D2.2 Social Validation Methodology

DELIVERABLE Project Acronym: SDI4Apps Grant Agreement number: 621129 Project Full Title: Uptake of Open Geographic Information Through Innovative Services Based on Linked Data

D2.2 SOCIAL VALIDATION METHODOLOGY Revision no. 06

Authors:

MAC - John O’Flaherty, Connor O’Reilly, Ed Keane CCSS - Irena Koskova, Josef Fryml HSRS - Karel Charvat SAZP - Martin Tuchyna SSSA - Cristina Marullo UWB - Tomas Mildorf, Otakar Cerba

Project co-funded by the European Commission within the ICT Policy Support Programme Dissemination Level P Public C Confidential, only for members of the consortium and the Commission Services

X

D2.2 Social Validation Methodology

Revision History Revision

Date

Author

Organisation Description

01

11/04/2014

John O’Flaherty

MAC

02

30/05/2014

John O’Flaherty Josef Fryml

MAC CCSS

03

11/07/2014

John O’Flaherty

MAC

04

17/09/2014

John O’Flaherty

MAC

05

30/09/2014

John O’Flaherty

MAC

06

30/09/2014

Tomas Mildorf

UWB

Initial draft based on desk research and DoW. Updates based on discussions at the project Kickoff Meeting on 15-16 April 2014, further desk research and subsequent Partners’ inputs. Update based on discussions at the project Technical Meeting on 9-10 June 2014, and Partners’ feedback and inputs on the Pilots in particular. Version for SDI4Apps review process. Final Version for submission, based on review feedback & further partners’ inputs. Minor changes of the document layout.

Statement of originality: This deliverable contains original unpublished work except where clearly indicated otherwise. Acknowledgement of previously published material and of the work of others has been made through appropriate citation, quotation or both. This project has received funding from the Union’s ICT Policy Support Programme as part of the Competitiveness and Innovation Programme. http://ec.europa.eu/digital-agenda/en/ict-policy-support-programme

Views expressed in this document are those of the individuals, partners or the consortium and do not represent the opinion of the Community. Copyright © 2014, SDI4Apps Consortium.

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© SDI4Apps Consortium 2014


Table of Contents Executive Summary......................................................................................7 1.

Introduction .......................................................................................8 1.1

SDI4Apps Project and Platform ..............................................................9

1.1.1

SDI4Apps Implementation .............................................................. 13

1.2

SDI4Apps Community Building and Social Validation ................................... 15

1.3

SDI4Apps User Communities ................................................................ 16

1.4

SDI4Apps Validation ......................................................................... 18

1.4.1

SDI4Apps Approach to User Validation ............................................... 18

1.4.2

Validation of Voluntary Data .......................................................... 20

1.5

SDI4Apps Indicators and Metrics ........................................................... 20

1.6

Open Geospatial Data ....................................................................... 22

1.7

Open Data Support........................................................................... 24

2.

Social Validation ................................................................................ 27 2.1

Social Spaces & Social Validation .......................................................... 29

2.1.1

Social Validation ........................................................................ 30

2.2

Social Validation criteria and indicators of success ..................................... 32

2.3

Future prospects and scaling-up ........................................................... 35

3.

Methods for multi-stakeholder analysis for internal & external communities ......... 38 3.1

SDI4Apps Stakeholders and User Groups .................................................. 40

3.1.1

SDI4Apps Stakeholder roles ............................................................ 40

3.1.2

SDI4Apps User Groups .................................................................. 42

3.1.3

User Engagement ....................................................................... 42

3.1.4

SDI4Apps Communities ................................................................. 43

3.2

SDI4Apps Stakeholders’ Service Layers ................................................... 45

3.3

SME Capacity building ....................................................................... 47

3.4

SDI4Apps Multistakeholder Evaluation Process .......................................... 48

4.

Sustainable operation of the SDI4Apps Framework ........................................ 50 4.1

Long term viability of SDI4Apps ............................................................ 51

4.1.1 4.2 5.

Future Challenges ....................................................................... 53

Source Licence Model ....................................................................... 54 SDI4Apps User Scenarios ....................................................................... 56

5.1

Scenarios ...................................................................................... 56

5.1.1 5.2

Using Scenarios in Usability Testing .................................................. 58

Easy Data Access Pilot....................................................................... 58

5.2.1

Easy Access Scenario 1: Mobile Apps to support Tourism for Conservation .... 60

5.2.2

Easy Access Scenario 2: Mobile App for Protected Heritage Sites ............... 66

5.3

Open Smart Tourist Data Pilot ............................................................. 72 Page 4 of 156


D2.2 Social Validation Methodology 5.3.1 5.4

Open Sensor Network Pilot ................................................................. 80

5.4.1 5.5

6.

Ecosystem Services Pilot Scenario .................................................... 98

Pilots’ requirements of the SDI4Apps Platform ......................................... 106 Success Criteria for the SDI4Apps platform for each User Scenario.................... 108

6.1

Convergence of Cloud and Open Source Computing ................................... 110

6.2

SDI4Apps Learning Community Space .................................................... 111

6.3

Multilingualism .............................................................................. 112

6.4

Criteria for the Evaluation of the SDI4Apps Tools for LOD pilot outputs ........... 112

6.5

Success Criteria of the SDI4Apps platform for each User Scenario .................. 119

7.

8.

Open INSPIRE4Youth Pilot Scenario .................................................. 93

Ecosystem Services Evaluation Pilot ...................................................... 97

5.7.1 5.8

Open Land Use Pilot Scenario ......................................................... 85

Open INSPIRE4Youth Pilot – Regional Atlas of the Environment ....................... 92

5.6.1 5.7

Open Sensor Pilot Scenario ............................................................ 80

Open Land Use Map through VGI Pilot .................................................... 84

5.5.1 5.6

Smart Tourism Pilot Scenario ......................................................... 74

SDI4Apps Social Validation Plan ............................................................. 123 7.1

SDI4Apps Social Validation Implementation ............................................. 124

7.2

Evaluation Plan Set-up ..................................................................... 126 Conclusions & Recommendations ........................................................... 128

Annex A:

Linked Open Data ...................................................................... 131

Global Open Data Initiative Declaration ........................................................ 137 Annex B:

SDI4Apps Scenario Templates ........................................................ 140

Use Case Template ................................................................................. 140 Guidance for Use Case Template .............................................................. 140 Dataset Template .................................................................................. 144 Guidance for Datasets Template .............................................................. 145 Application Template .............................................................................. 148 Guidance for Application Template ........................................................... 148 Annex C:

Draft Agenda for Stakeholder Workshops........................................... 150

Annex D:

List of Abbreviations ................................................................... 153

List of Figures Figure 1 SDI4Apps Platform .......................................................................... 10 Figure 2 SDI4Apps Pilot Applications ................................................................ 11 Figure 3 SDI4Apps System Architecture and Operational Layers ................................ 12 Figure 4 SDI4Apps Approach to User Validation ................................................... 19 Figure 5 Open Data Support services ............................................................... 25 Page 5 of 156


D2.2 Social Validation Methodology Figure 6 SSRI 5 elements: policy, market, society, infrastructures and technology ......... 30 Figure 7 SSRI mapping of TRLs & Testing based on Openness, Maturity & grade of Design. 30 Figure 8 Living Lab approach to impact assessment within the process of social validation34 Figure 9 Social Validation ‘ideal types’ in SDI4Apps .............................................. 36 Figure 10 SDI4Apps Impact assessment process ................................................... 39 Figure 11 The ICT-ENSURE stakeholder mapping. ................................................. 41 Figure 12 SDI4Apps Pilots Added Value Schema ................................................... 42 Figure 13 ICT-ENSURE layered model of ICT relevance .......................................... 45 Figure 14 Layered ICT infrastructures and services............................................... 45 Figure 15 SDI4Apps-based infrastructure and service layers. ................................... 46 Figure 16 Territorial Innovation Interactions ...................................................... 52 Figure 17 Catalogue client result list, metadata detail and map portrayal. .................. 60 Figure 18 Cloud Service Models .................................................................... 106 Figure 19 Current costs & benefits of European SDI (A) and the targeted situation (B).... 108 Figure 20 New paradigm in data collection. ...................................................... 109 Figure 21 Problem of two worlds. .................................................................. 110 Figure 22 Learning Community Space ............................................................. 112

List of Tables Table 1 SDI4Apps Project Performance Monitoring Table ....................................... 21 Table 2 SDI4Apps Pilots & Validation Approaches ................................................. 33 Table 3 SWOT of managing the SDI4Apps Communities .......................................... 44 Table 4 Interoperation between Pilots ............................................................. 56 Table 5 SDI4Apps Cloud Service requirements ................................................... 106 Table 6 SDI4Apps Functionality Enablers required by the Pilots ............................... 107 Table 7 SDI4Apps pilots mapped by the platform’s Tools’ Criteria............................ 117 Table 8 Validation approach & Initial mapping of each Pilot’s Success Criteria ............ 119 Table 9 SDI4Apps Tools’ Requirements Criteria .................................................. 122 Table 10 SDI4Apps Social, Technical & Validation Activities ................................... 125 Table 11 Major Aims of the SDI4Apps project .................................................... 125 Table 12 SDI4Apps Social Validation Plan execution & actions ................................ 126

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EXECUTIVE SUMMARY SDI4Apps aims to bridge the gap between the top-down managed world of INSPIRE, Copernicus and GEOSS and the bottom-up mobile world of voluntary initiatives and thousands of micro SMEs and individuals developing applications based on GI, by adapting and integrating experience from previous projects and initiatives to build a cloud based framework with open API for data integration, easy access and provision for further reuse. The solution will be validated through six pilot applications focused on easy access to data, tourism, sensor networks, land use mapping, education and ecosystem services evaluation. This report defines criteria for measurement of success of the SDI4Apps platform methods for multi-stakeholder social validation and analysis for internal and external communities and also a set of indicators, which will be measured during the validation process based on an initial structured description of the pilot scenarios. The recommendations section summarizes the main issues for the project partners as well as external stakeholders. Keywords:

Social Validation, Use Cases, Pilots, Scenarios, Users, Communities

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1. INTRODUCTION The potential of geographic information (GI) collected by various actors ranging from public administration to voluntary initiatives of citizens is not fully exploited. The advancements of ICT technologies and shift towards Linked Open Data (LOD) gives an excellent foundation for innovation based on reuse of GI. The establishment of Spatial Data Infrastructures (SDI) has largely been driven by the “traditional” GI community and the national and European policies governing this sector. However now GI is no longer a separate information space but finds itself part of a larger European information space where the ultimate objective is the creation of value-added services based on use and reuse of public sector information as defined by the PSI and INSPIRE Directives rather than exchange of “layers” between different GI software. Establishing an infrastructure to meet this new and wider objective puts greater strain on local authorities and institutions that traditionally were users of GI but now find themselves in an environment where they are expected to be data and service providers, a role that is far more demanding in terms of technical knowledge and resources. The main target of SDI4Apps is to build a cloud based framework that will bridge the gap between 1) the top-down managed world of INSPIRE, Copernicus and GEOSS, built by SDI experts, and 2) the bottom-up mobile world of voluntary initiatives and thousands of micro SMEs and individuals developing applications (apps) based on GI. SDI4Apps will adapt and integrate experience from previous projects and initiatives such as HABITATS 1, Plan4business 2 and EnviroGrids 3, to build its cloud based platform with an open API for data integration, easy access and provision for further reuse. The solution will be validated through six pilot applications focused on easy access to data, tourism, sensor networks, land use mapping, education and ecosystem services evaluation. SDI4Apps aims to ensure that users profit from INSPIRE, and that INSPIRE profits from different voluntary initiatives. This report defines criteria for measuring the success of the SDI4Apps platform, methods for multi-stakeholder social validation and analysis for internal (i.e. SDI4Apps project partners) and external communities, and also a set of indicators, which will be measured during the validation process based on an initial structured description of the pilot scenarios. A social validation plan is described, to setup the evaluation and define the metrics that will be performed, and a timetable for actions is scheduled in order to check the completeness and execution of the plan. The initial social validation work has identified success criteria according to the different standpoints represented in each user scenario, and a framework for evaluating the added value of services that conform to the standards proposed by SDI4Apps. The indicator sets thus defined are then aggregated into a multi-stakeholder model of the problem settings for the main scenarios, starting from the validation pilot settings, in the context of a dynamic representation of the overall systemic impact of the SDI4Apps platform on business, citizens, decision-making and policy formulation capacity. This in turn will lead to the definition of strategies for scaling-up the results of the SDI4Apps sustainability strategy building in WP8 (Dissemination and Business Planning). 1 www.inspiredhabitats.eu 2 www.plan4business.eu 3 www.envirogrids.net Page 8 of 156


D2.2 Social Validation Methodology Annex D lists the abbreviations used in this report.

1.1 SDI4Apps Project and Platform The objectives of the SDI4Apps project are to: 1) integrate a new generation of spatial data infrastructure (SDI) based on user participation and social validation, 2) support easy discovery and accessibility of spatial data for everybody, 3) link spatial and non-spatial data using Linked Open Data principles, 4) support multilingualism of spatial data, 5) build a scalable cloud based infrastructure for support of SDI initiatives and Location Based Services (LBS), 6) integrate in-situ measurements and Earth observation data, 7) design an open Application Programming Interface (API) supporting integration of spatial data and LBS into applications developed and deployed by non-GI developers, 8) integrate a demonstration set of pilot applications, 9) test new approaches for data sharing by users through pilot applications, 10) attract external developers (mainly from SMEs, students and researchers) to test the newly integrated platform, 11) organise contests for application developers supporting wider use of GI data, 12) build a sustainable business model for the SDI4Apps cloud based platform. SDI4Apps will adapt and integrate experience from previous projects and initiatives such as Plan4Business 4 and HABITATS 5 to build a cloud based platform with an open API for data integration, easy access and provision for further reuse. SDI4Apps aims to build a win-win strategy for building a successful business for European SMEs by bringing existing INSPIRE, Copernicus, GEOS and voluntary based information to different user groups, including: • SMEs, students and researchers developing new apps, • local and regional NGOs and other organisations dealing with sustainable development of regions, • local businesses that can benefit from spatial data and spatial apps, • local communities contributing to the regional sustainable economic and social development via supporting tourism related activities, • citizens, mainly young people, using smart devices and web applications, • policy makers and public servants – through better exploitation of voluntary data. SDI4Apps aims to address their needs, including: • spatial data in a standardised form and easy to access, • better exploitation of GI data from various sources both from the public and voluntary domains, • reliable data and sustainable data sources, • education on how to use GI data. The SDI4Apps cloud based platform to provide these aims and objectives will be accessible to everyone at three levels: 1) A set of mainly OGC based interfaces for developers using the SDI4Apps platform for brokerage giving access to harmonised GI and non-GI data. Platform as a Service, (PaaS)

4 5

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D2.2 Social Validation Methodology 2) Access for developers using the SDI4Apps Application Programming Interface (API), Software as a Service (SaaS). 3) SaaS Cloud Solution - access to final users using applications, delivered as services.

Figure 1 SDI4Apps Platform The SDI4Apps content will consist of a combination of various types of existing data sources that will be harmonised: • existing Volunteered Geographic Information (VGI) data, such as for example OpenStreetMap, • pan-European public data such as data from the European Environmental Agency (EEA), including CLC, Urban Atlas, Natura2000, Soil data, water catchment data, etc.), • data coming from previous projects, mainly EnviroGRIDS, HABITATS, Plan4business and Plan4all 6, • INSPIRE based Open Data, • newly generated in-situ data, • Earth observation data, • data from project partners, • open non-GI data from different sources, such as EUROSTAT and national repositories, • Linked Open Data from social networks, • VGI data collected within the project. The SDI4Apps project will integrate a cloud-based platform for data reuse. On that platform, several apps (pilot apps) will be designed and implemented.

6 www.plan4all.eu Page 10 of 156



Figure 2 SDI4Apps Pilot Applications The envisaged pilots include: 1) Easy Data Access - will support easy access to existing services and will integrate an API solution, which will support easy collection of information using smart phones and integrate this information into current SDIs. 2) Open Smart Tourist Data - will support related business issues such as easy integration of the SDI4Apps system into proprietary solutions (thanks to the implementation of standards), reusing and sharing existing information resources, channels and tools. Open Smart Tourist Data will integrate users’ data, free and open global data, SDI4Apps Team’s data, crowdsourced data and social media. 3) Open Sensors Network - will create an environment where different groups of volunteers (for example farmers) will be able to integrate low cost sensors (meteorological, quality of air, etc.) into local and regional web sensor networks. 4) Open Land Use Map Through VGI - an initiative for voluntary Open Land Use Mapping. 5) Open INSPIRE4Youth - to generate local educational multilingual environmental and cultural heritage applications for students and youth. 6) Ecosystem Services Evaluation - on the identification of spatial representation of the outcomes of EcoSystem Services (ESS) Evaluation with a focus on the support of tourism. The SDI4Apps infrastructure, which will be hosted in the national Centre CERIT-SC (CERIT Scientific Cloud) of the Masaryk University (MU), will have the following architecture:

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Figure 3 SDI4Apps System Architecture and Operational Layers The SDI components will be based on technologies, not only from the HABITATS, BRISEIDE 7, Plan4all 8, Plan4business and EnviroGRIDS 9 projects, but also on solutions used in the Czech and Slovak INSPIRE geoportals 10. The technologies will be merged and transferred into a cloud environment. On top of this technological solution an open API will be defined for use with both desktop and mobile solutions. SDI4Apps believes that future data strategy is not about necessarily trying to understand every data point, but rather how to use technology to make data, both big and small, actionable. Data is actionable when it is accessible, machine-readable, deliverable at web scale, relevant, and open. • Accessible: available to be queried on-demand via an API • Machine-readable: in a format (e.g., JSON) that machines can consume

7 www.briseide.eu 8 www.plan4all.eu 9 www.envirogrids.net 10 See http://best-practices.smespire.eu/practices/74/national-inspire-geoportal-of-the-czechrepublic and http://best-practices.smespire.eu/practices/47/national-geoportal-gateway-to-slovaksdi Page 12 of 156


D2.2 Social Validation Methodology • • •

Web scale: capable of being delivered reliably regardless of the volume or velocity of data requests Relevant: driving revenue or affecting an operational decision Open: available for self-service access whereby a developer can register with the data provider, accept their terms of use and obtain data programmatically.

A key part of the project, to which its Social Validation activities will directly contribute, is business modelling and ensuring that the results will have wide uptake. The SDI4Apps business model that will guarantee long time sustainability, will be based on the Freemium model 11 where core services are given away for free and premium (advanced) proprietary services are sold. An analysis of results from previous projects will be performed and a model that can be applied by SMEs and other parties will be designed and tested in WP8 (Dissemination and Business Planning).

1.1.1

SDI4Apps Implementation

The SDI4Apps Infrastructure will be implemented through technological integration that will include: 1. Proven architecture frameworks from previous work, extended by geospatial tools supporting integration of existing information sources, data collection, data analysis, data visualisation and data access. 2. Further development of the INSPIRE, GMES, GEOSS and SISE initiatives by incorporating concepts and results from cloud computing, Future Internet projects (such as FI-WARE) and the Internet of Things (IoT). 3. Establishment of an open and interoperable collaborative platform for all stakeholders to exchange information and base decision-making on validated data. 4. Supporting the building of workflows based on existing components. 5. Supporting a robust security solution. 6. Defining an Open API supporting easy development of new applications by third parties. 7. Ensuring that all actors can access this information when engaged in decision making processes and to ensure the existence of feedback loops between the actors and the analytical module. 8. Ensuring that the integrated tools and platforms are not only useful in dealing with present day challenges, but that they will be able to morph in such a way as to be useful in dealing with future challenges. 9. Defining an adaptive data fusion model, which in a distributed manner will allow conserving the energy of sensors and maximizing the lifetime of sensor networks. Data fusion and management based on different varieties of crops and different geographic location and environments gives higher accuracy and robustness. For the SDI4Apps architecture the following principles will be applied to set up a commonly designed infrastructure: • Accessibility • Scalability • Multilingualism • Security • Privacy • Use of Open Standards While data harmonisation and the development of interoperable services must take into account the current operational practices of end-users, the SDI4Apps project will analyse the relevant standards and combine these standards with the needs of spatial planning. 11 http://en.wikipedia.org/wiki/Freemium Page 13 of 156


D2.2 Social Validation Methodology The focus will also be on an optimal combination of commercial and open source platforms to reuse existing solutions. SDI4Apps functionality will be based on standards defined in the INSPIRE implementation rules to ensure maximum interoperability and extensibility around Europe. The most important standards for geospatial information are the ISO 19100 series and Open Geospatial Consortium (OGC) standards. The SDI4Apps platform will be built on a service oriented architecture (SOA) and for the widest take-up and use, and will be mainly open source 12. The IPRs of existing solutions from SDI4Apps partners are covered in the Consortium Agreement. SDI4Apps will actively cooperate with the OGC (Partner HSRS is an OGC member) and give feedback for new standards. SDI4Apps will also establish links with W3C activities in relation to Linked Open Data. Open Data SDI4Apps will follow the European Strategy for Open Data 13 and use the EU Open Data Portal and Support 14. A key aim of SDI4Apps is to turn open spatial and spatial related data (data with no direct references) into business. This will be achieved through its hub of services, which will make Open Data easily discoverable and easily accessible. The SDI4Apps cloud API will support easy integration of this data into diverse services. It will also support better transparency of public services. Availability of public data will enable citizens to better monitor administrative processes. SDI4Apps will also support evidence-based policy making and administrative efficiency. Through innovative applications administrations will have possibilities to use better knowledge coming from open data. SDI4Apps will also establish links with the European Union Open Data Portal 15 and Pan European data portal 16 as the single points for EU open public data and with the INSPIRE Geoportal 17. SDI4Apps will also cooperate with global initiatives such as the FAO initiatives Agrovoc 18 and Agris 19. All data that will be generated by SDI4Apps will be open, unless the owners of some source data requires it to be otherwise 20. However integration of such non-open sources will be rare and only considered for use if there is a compelling reason, for instance, a local planning app in a particular region. Linked Open Data Linked Open Data (LOD) enables a new quality in terms of better accessibility and interconnection 21. LOD is a specific focus of SDI4Apps and the aim is to demonstrate the advantages of its use in different domains such as tourism and environmental protection. The focus of SDI4Apps will not be only on linkage of spatial data with non-spatial data, but also on linkage of different spatial layers and building of new semantic understandings of spatial data interrelation. Previous experiments have demonstrated that this is not effectively possible without scalable computational capacities and SDI4Apps will demonstrate the advantage of cloud computing for this approach.

12 As agreed at the project Kickoff Meeting, on 15-16th April 2014. 13 www.iprhelpdesk.eu/node/690 14 http://open-data.europa.eu/en/data/ and https://joinup.ec.europa.eu/community/ods/description. 15 http://open-data.europa.eu/en/data/ 16 http://publicdata.eu/ 17 http://inspire-geoportal.ec.europa.eu/ 18 http://aims.fao.org/standards/agrovoc/about 19 http://agris.fao.org/agris-search/index.do 20 As agreed at the project meeting, on 17th September 2014. 21 An introduction to Linked Data and its implementation is given in Annex A. Page 14 of 156


D2.2 Social Validation Methodology Security and privacy issues SDI4Apps, like all INSPIRE initiatives, relies on the opening up of mainly public databases and their interconnection with public and private systems in a web services logic. This raises security and privacy issues for which policies within the participating public administrations are already in place and fully functional. SDI4Apps will work within the framework of these policies, following in general the recommendations and guidelines of ENISA (European Network and Information Security Agency) 22 and the Privacy Directive 2002/58/EC 23.

1.2 SDI4Apps Community Validation

Building

and

Social

This report documents the results of Task T2.2 “Social Validation Methodology” in the project’s WP2 “Community Building and Social validation”. The aim of WP2 is to build the SDI4Apps user community that actively participates in the processes of design, integration, validation and uptake of the proposed SDI4Apps platform. Its specific objectives, as defined in the DoW, are: 1. Community building and management with a focus on pilot regions and potential external users and developers: • launch and maintain the SDI4Apps network for the consolidation of its user communities and their structured participation in key project activities; • engage stakeholders involved in SDI4Apps pilot services on the one hand, and participants in the extensive thematic, global and trans-European networks represented by project partners on the other hand, in active participation in the SDI4Apps communities; • with the SDI4Apps communities, develop use scenarios exploiting the availability of harmonised and interoperable data sets and services for accessing INSPIRE related data by large community 2. Define a validation methodology for internal and external validation of the platform on the basis of the project results and especially the outcomes of the validation pilot services, assess the potential impact of up-scaled adoption of SDI4Apps metadata profiles, data models and SDI services on concrete environment-related activities they carry out in their daily work 3. Support the validation of the system by internal user groups and tools and methods by external communities and provide feedback for the technical teams The work of Task T2.2 that directly generated this report, aimed to deliver a social validation plan for the project, gathering evaluation requirements from other WPs and specifying the evaluation set-up and metrics to be performed. In particular the aim was to define: • criteria for measurement of success of the SDI4Apps platform, according to the different standpoints represented in each of the pilots’ user scenarios, as the framework for evaluating the added-value of services that conform to SDI4Apps standards. • methods for multi-stakeholder analysis for internal and external communities, • a set of indicators, which will be measured during the validation process in WP6. The indicator sets thus defined will be aggregated into a multi-stakeholder model

22 23

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•

of the problem settings for the main scenarios, starting from the validation pilot settings, in view of a dynamic representation of the overall systemic impact of the SDI4Apps platform on business, citizens, decision-making and policy formulation capacity. This in turn will lead to the definition of strategies for scaling-up results of the SDI4Apps sustainability strategy building.

1.3 SDI4Apps User Communities SDI4Apps will build user communities that actively participate in the processes of design, integration, validation and uptake of the proposed SDI4Apps cloud platform. The specific operational objectives include: •

community building and management with a focus on pilot regions and potential external users and developers: - launch and maintain the SDI4Apps network for the consolidation of its user communities and their structured participation in key project activities; - engage stakeholders involved in SDI4Apps pilot services on the one hand, and participants in the extensive thematic, global and trans-European networks represented by project partners on the other hand, in active participation in the SDI4Apps communities; - working with the SDI4Apps communities to develop user scenarios exploiting the availability of harmonised and interoperable data sets and services to access INSPIRE related data by a large and extended community;

•

define a validation methodology for internal and external validation of the platform - on the basis of the project results and especially the outcomes of the validation pilot services, assess the potential impact of scaled-up adoption of SDI4Apps metadata profiles, data models and SDI services on environment-related activities that they carry out in their daily work;

•

support the validation of the system by internal user groups and tools and methods by external communities, and provide feedback for the technical teams.

The SDi4Apps approach brings together the demand-driven power of the market-oriented solutions and the institutional legitimacy of INSPIRE/OD/LOD, which places the public interest before commercial needs. The approach is based on social validation, a process which engages “those who will adopt” within institutionally framed pilot experiments in 6 diverse pilots. Social validation in SDI4Apps’ six pilots is supported by an analytical and multi-perspective framework, responding to key issues such as: · • The social significance of stated goals · • The social appropriateness of the procedures that are followed • The social importance and impact of obtained effects Thus central to validation of the SDI4Apps pilots are actions aiming to both build individual and collective assets by better understanding and potentially improving the effectiveness and transparency of the interaction amongst different organizational and institutional contexts which govern the use of these assets. The project covers a range of assets in its validation pilots such as natural resources management on which local communities depend. To that end, SDI4Apps identifies with stakeholders’ specific usage scenarios, including the state of the art baseline and user requirements coming from the validation pilots. These represent the key input for the planned data and metadata modelling activities and the SDI/LOD services that will have been developed in the project. Page 16 of 156


D2.2 Social Validation Methodology As the HABITATS project found 24, the main benefits of this approach will emerge through the need to interact with key stakeholders and the possibility of providing a better service to specific user groups. Therefore the SDI4Apps project offers different connecting points to provide a link between the SDI4Apps platform developments and the local data providers and users. Within its core community, the six SDI4Apps’ validation pilots represent the basis for the social validation process. In addition to strengthening “real-life” communities, these interest groups will also participate in online communities as well to discuss experiences on a local, national or international scale. Thus representing the core community of the SDI4Apps’ project will be a key component in the wide range of cross-country and crosspilot community of domain experts, with practitioners and policy makers. These pilot communities will be predominantly involved through participatory methods and approaches to social innovation. Against this background, SDI4Apps will demonstrate the benefits of its cloud-based GI/LOD platform in practice, or aspects that hinder it, by involving different user communities. Consequently, the methodological approach in SDI4Apps is to relate the social validation process to the critical learning path of current and future developments in the validation pilots. In order to reach its main objective, SDI4Apps aims to operationalise a range of public and private services that require the use of open and linked spatial environmental data, enabling those services to access the required information because it has been harmonised and made available according to a common format. In this regard, the project has the following operational objectives: •

To build User Communities of the stakeholders involved in both the demand and supply of the spatial information and services, involve these communities in the development of usage scenarios and requirements and in a structured analysis of the SDI4Apps scenarios’ impact on participatory standards construction processes and, more specifically, on the effectiveness of their daily environmental related activities.

•

To build on previous and ongoing results and experiences in INSPIRE standardisation and SDI deployment, but also transfer experience from existing successful implementations such as the Czech and Slovak Geoportals.

•

To define an open but efficient architecture for discovery, visualisation, transformation and processing of environmental data stored and maintained in services distributed throughout Europe and the world, based on INSPIRE and/or OD principles allowing bidirectional interfaces with user services both in accessing data and capturing user-generated VGI; to deploy specific service apps as required by the ongoing validation pilots; and to finally develop a service toolkit for the longterm development of new services within the framework of the common cloudbased architecture.

•

To set up and run a coherent set of application pilots within the concrete user scenarios and based on existing stakeholders, services and information sources, using fast prototyping to enhance those services as developments of the user scenarios, integrating the SDI4Apps platform for on-demand access to distributed sources of GI and other data; to thus validate the robustness, relevance and added value of the SDI4Apps platform in supporting concrete services of environmental relevance.

24HABITATS D2.4.1 Impact Assessment, May 2012, available at http://www.inspiredhabitats.eu/index.php?option=com_docman&task=doc_download&gid=12&Itemi d=82 Page 17 of 156



1.4 SDI4Apps Validation Before the SDI4Apps components will be available for the community at large, there will be extensive internal technical testing by project partners of all components, including: • Testing and quality assurance of integrated sub-systems and components towards the overall user-requirements; • Resolution of problems identified throughout the testing activities. SDI4Apps’ validation will also take into account important issues such as functionality, usability, performance, accessibility, scalability, location independence, but also privacy and security, and will include •

Internal Validation, by SDI4Apps partners, which will be focused on 1. indicators measuring usability of the SDI4Apps components by developers in year one. 2. usability of pilot applications by end users in year two. 3. usability of pilot applications by end users and new possibilities for developers in year three

•

External Validation, by users who are not partners in the project, which will be focused on 1. usability of newly developed APIs for external users in year two. 2. external use of the tools, API, data pools and applications by end users in year three.

The different categories of users, such as specialists, policy makers, stakeholders, community users, will access the SDI4Apps resources and features by local and global decision making tools and applications. The open cloud-based SDI4Apps platform will include both basic and extended functionality supporting: 1. Data harmonisation 2. Linked Open Data 3. Multilingualism 4. Advanced visualisations 5. Integration of mobile apps 6. Analytical and modelling API 7. Scalable execution of spatial models 8. Data analysis 9. Interoperability between local and global geospatial models. An important objective is to define the testing methodology and regular testing of all of the advanced SDI4Apps tools. This will be undertaken in WP4. While WP6 (Internal Pilot Applications) will validate the SDI4Apps framework and tools through the deployed pilot demonstrators, with a special focus on evaluating: • the effectiveness of the approach for the cloud, LOD and semantic services; • how well the proposed architecture can be adapted to different scenarios. • the limitations and benefits of the approach in comparison to existing technologies.

1.4.1

SDI4Apps Approach to User Validation

The SDI4Apps team combines partners covering the entire chain from data providers, technological developers and geospatial data experts to final end users. The consortium includes partners involved in Living Labs which will be part of the overall methodology for the platform integration and social validation. The Living Labs approach, as an essential building block of SDI4Apps, is aimed to structure wide-spread end-user participation in new technologies’ integration and adoption, and in research and new innovation activities.

Page 18 of 156


D2.2 Social Validation Methodology The SDI4Apps methodology will not follow a standard structure of pilot projects shown in the following sequence of actions: User requirements  Design 

Development  Deployment  Testing

Instead SDI4Apps will follow a different approach, as: 1. The majority of EU projects are collecting new requirements which in most cases overlap, 2. There already exists many implementations of state of the art technologies, and user requirements collection is not leading to any progress, 3. Users are interested in getting results as soon as possible, and standard project methodologies do not deliver satisfying results in time. For these reasons the SDi4Apps will use the following very different user-driven approach: (1)     

Deployment of SDI4Apps Cloud platform (state of art technologies, Open Tools) (2) User experimentation and social validation in real-world scenarios (3) Feedback from the SDI4Aps community (4) Redesign (5) Improvement of the SDI4Apps Cloud Framework (6) User experimentation and social validation in real-world contexts  (2)

Figure 4 SDI4Apps Approach to User Validation In particular, SDI4Apps will extend to the cloud, the approach of the Reference Laboratory introduced by the HABITATS project 25. The Reference Laboratory is an environment with an open API based on Open Source components. This platform, which is an extension of the current INSPIRE architecture, incorporates basic principles of neogeography 26 and Volunteered Geographic Information (VGI). These techniques will be used as the main building blocks of the SDI4Apps social validation. It allows users and data providers to test existing technologies, customise solutions for their purposes and thereby generate further research tasks through user-driven processes. The Platform will also collect information coming from other projects as an input for analysis and discussions within the SDI4Apps social validation process. The developments of the project will follow two iterative cycles that lead through different aspects of SDI4Apps: 1. At the first stage, users will use current APIs and Open Source components coming from EnviroGrids, HABITATS and Plan4business to test the development of new 25 www.habitats.cz 26 the use of geographical techniques and tools for personal and community activities or by a nonexpert group of users, see http://en.wikipedia.org/wiki/Neogeography Page 19 of 156


D2.2 Social Validation Methodology applications implementing neogeography principles & VGI in their pilot applications. 2. Feedback will be collected and used by developers to improve the components. The R&D community will have real requirements, coming from practical experimentation. During the adoption of these new requirements the user community will continually test the new solution. As such, the interactive interlinking of the activities performed involves different user communities being identified and brought together, while the pilot user communities use the platform for dissemination and awareness raising activities. Then an impact assessment will lead to a framework definition that again supports the further improvement of SDI4Apps.

1.4.2

Validation of Voluntary Data

Task T5.2 (Methodology for Quality Assessment of Voluntary Data) will concentrate on methodologies to assess the reliability and usability of the VGI data that will be much used in the project. Based on the research of existing classifications and methodologies, an existing, new or modified approach will be integrated. This will be based on a Quality Assurance Project Plan (QAPP) which will be defined to ensure that collected data and analyses meet the project requirements. The QAPP will include: • Quality Assurance (QA) – which refers to the overall management system which includes the organisation, planning, data collection, quality control, documentation, evaluation and reporting activities of volunteers; • Quality Control (QC) – which refers to the routine technical activities whose purpose is essentially, error control; • Precision - as the degree of agreement between repeated measurements of the same characteristic on the same sample or on separate samples collected as close as possible in time and place; • Accuracy - is a measure of confidence in a measurement; • Representativeness - is the extent to which measurements actually depict the true environmental condition or population that is evaluated; • Completeness - is a measure of the number of samples that must be taken to be able to use the information, as compared to the number of samples that were originally planned to be taken; • Comparability - is the extent to which data from one study can be compared directly to either past data from the current project or data from another study; • Detection Limit - can apply to monitoring and analytical instruments as well as to methods; • Measurement Range - is the range of reliable measurements of an instrument or measuring device.

1.5 SDI4Apps Indicators and Metrics The primary objective of SDI4Apps is to move current public SDIs based on the INSPIRE Directive towards businesses and citizens. The goal is to support building new types of applications, but also to enable SME developers and non-GI specialist to integrate public spatial data into their applications. SDI4Apps will deploy existing technologies as hubs for accessing spatial and non-spatial data on the cloud. Its main contribution consists in an innovative approach to the development of a regional infrastructure using social validation and new approaches to SDI by integrating OD, LOD, VGI and neogeography. The combination of various sources of data will provide sufficient Page 20 of 156


D2.2 Social Validation Methodology amounts of information for all participants of regional development (providers as well as clients). The results of the project (methodologies of data collecting and processing, data models, business procedures, software components, client interface and open API) will enable many opportunities to improve the operation of organisation focused on data and information processing in the environment: • Using principles of social validation for testing new technologies in the context of the Future Internet. • Time savings connected with implementation of newly developed methodologies, catalogues of existing data sources and voluntary data collections. • Financial savings related to re-using free components and free or open-source data sets and web services. • Open opportunities to promote existing forms of tourism as well to establish and promote (in a very effective way) new tourism activities, leading to new visitors, new job opportunities and further development of SMEs developers. • Benefits following from the harmonisation of environmental information at all levels (local, regional, global). These benefits are connected with sharing of information to save financial resources, but also to satisfy user requirements. The implementation of results of the project can contribute to an improvement in environment protection in Europe. While informed citizens will use the new SDI4Appsenabled services, to better contribute to environmental protection. The SDI4Apps projects indicators and metrics as listed in the DoW are as follows: Objective /expected result Data oriented indicators 1 WP5 2 WP5 3 WP5 4 WP5 5 WP5 Social, dissemination and 6 WP8 Indicator No.

7

WP8

8

WP8

9

WP8

10

WP8

Indicator name

improvement factor of analytic queries

WP5

15

WP7

Year 2

100 20 50 20 10

500 50 200 50 30

1,000 200 500 200 50

2,000

4,000

10,000

Number

100

200

500

Number

100

500

1,000

Number

4

4

4

Number

10

20

30

Number Number

0

15

40 30

No.times process speeds up Number

X5

X10

X20

10,000

50,000

100,000

1

5

50

of datasets in the hub harmonised data sets of external LOD sets of streamed data sets of VGI data sets

website visitors No. of event participants in reporting period No. of registered users on mailing list, network sites and the platform No. of Press Releases in reporting period No. of publications in reporting period No.of sprint code participants No.of contest participants

No.of API calls/accesses per month No. of external applications

Expected Progress Year 1

No. of data No. of data No. of data No. of data No. of data exploitation oriented indicators: No. of unique monthly Number No. No. No. No. No.

11 WP7 12 WP7 Technology oriented indicators: Performance 13 WP4 14

Method of measurement

Number

sets sets sets sets sets

Year 3

Table 1 SDI4Apps Project Performance Monitoring Table

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1.6 Open Geospatial Data Open public data resources for re-use is one of the key priorities of the Digital Agenda for Europe. Data available in public European organisations have an enormous potential economic growth. Nevertheless, finding and accessing environmental information isn’t always straightforward. SDI4Apps will make spatial data easier to discover and use, having a positive impact on the public and standard availability of data according to the Linked Open Data Strategy for the purpose of environmental information. The WP6 pilots will involve SMEs focusing on human activities (e.g. tourism, environment). This availability will allow global environmental issues to be addressed, that are not possible at this moment due to costs, efficiency and sustainability. Producing and updating geospatial data is expensive and resource intensive. Hence, it becomes crucial to be able to integrate, re-purpose and extract added value from geospatial data to support decision making and management of local, national and global resources. Spatial Data Infrastructures (SDIs) and the standardisation efforts from the Open Geospatial Consortium (OGC) serve this goal, enabling geospatial data sharing, integration and reuse among Geographic Information Systems (GIS). Geospatial data are now, more than ever, truly syntactically interoperable. However, they remain largely isolated in the GIS realm and thus absent from the Web of Data. Linked data technologies enabling semantic interoperability, interlinking, querying, reasoning, aggregation, fusion, and visualisation of geospatial data are only slowly emerging 27. The vision of SDI4Apps is to leverage geospatial data as first-class citizens in the Web of Data, in proportion to their significance for the data economy. Currently, there are three major sources of open geospatial data on the Web: 1. Spatial Data Infrastructures, 2. Open data catalogues, 3. Crowdsourced initiatives. Spatial Data Infrastructures (SDIs) were created to promote the discovery, acquisition, exploitation and sharing of geographic information. They include technological and organisational structures, policies and standards that enable efficient discovery, transfer and use of geospatial data using the web 28 . R&D in this field is closely tied to standardisation activities led by international bodies, namely the ISO/TC 211 29, OGC 30 and W3C 31. In Europe, the INSPIRE Directive follows the OGC open standards, and has defined common data models for a number of application domains, such as hydrography, protected sites and administrative units, to enhance interoperability of spatial data sets of the different European countries 32. It provides the legal and technical foundations to ensure member state SDIs are compatible and usable on a transnational context. The major open standard Web services regarding discovery and querying of geospatial data in SDIs are OGC’s Catalogue Service and Web Feature Service (WFS) respectively. The first allows the discovery of geospatial data based on their metadata (e.g. scale, coverage) and the second enables querying of geospatial data. Additional standards provide visualisation and access to maps and tiles (Web Map Service, Web Map Tile Service, Keyhole Markup 27 See Annex A for a discussion on Linked Data. 28 D. Nebert. Developing spatial data infrastructures: The SDI cookbook. Technical report, on Global Spatial Data Infrastructure, 2004. 29 ISO /TC 211 Geographic Information/Geomatics, http://www.isotc211.org 30 Open Geospatial Consortium, http://www.ogc.org 31 W3C, http://www.w3.org 32 EC. Inspire directive, 2009. http://inspire.jrc.ec.europa.eu/ Page 22 of 156



Language, (Web Coverage Services) and enable developers to programmatically invoke

and compose complex geospatial analysis services (Web Processing Service). Currently practically all GIS and geospatial databases are fully compatible with these standards; GIS users can consume geospatial data from SDIs and publish geospatial data to SDIs in a relatively straightforward way. On a practical level, SDIs must be considered as having developed over time and are now becoming more stable data infrastructures. They represent a significant investment from the public and private sectors worldwide and are the basis for interoperability among significant scientific domains. Further, they constitute the most prominent source for high-quality open geospatial data. Thus, any contribution and advancement must either be directly involved in standardization efforts, or be based solely on existing standards, without directly affecting their applications. Crowd sourced geospatial data are emerging as a potentially valuable source of geospatial knowledge. Among various efforts perhaps OpenStreetMap and Wikipedia are the most significant. Providing a large variety of data, OpenStreetMap (OSM) 33 has become an important platform for mapping, browsing and visualising spatial data on the Web. OSM data is available in different formats 34 which can be imported into a database for its usage; it also provides web services to do search by name and inverse geocoding functionality. The benefits of semantic technology for spatial metadata and data management are numerous and varied. For example, ontologies have been used in the form of taxonomies on thematic web portals (e.g. habitat or species taxonomies, categories of environmentally sensitive areas, or hierarchical land use classifications). The role of these ontologies is however limited. They provide background knowledge, but only in some experimental prototypes are they used for constructing search requests or for grouping of search results into meaningful categories. Further, in experimental settings, there are examples of using the Web Ontology Language (OWL) 35 for bridging differences in conceptual schemas 36. The role of ontologies and knowledge engineering in these prototypes is basically to provide methodologies for integration and querying 37. Ontologies have played an important role in structuring data of geospatial domains 38 . However, semantic technology has not yet influenced spatial data management, and mainstream GIS tools are not yet extended with semantic integration functionality. Early work included the Basic Geo Vocabulary 39 by the W3C, which enabled the representation of points in WGS84 40 , and GeoRSS 41 which provided support for more 33 http://www.openstreetmap.org/ 34 http://wiki:openstreetmap:org/wiki/OSMfileformats 35 http://en.wikipedia.org/wiki/Web_Ontology_Language 36 E.g. Catherine Dolbear and Glen Hart. Ontological bridge building - using ontologies to merge spatial datasets. In AAAI Spring Symposium: Semantic Scientfic Knowledge Integration, pages 15{20. AAAI, 2008. 37 See for example Tian Zhao, Chuanrong Zhang, Mingzhen Wei, and Zhong-Ren Peng. Ontologybased geospatial data query and integration. In GIScience, volume 5266 of Lecture Notes in Computer Science, pages 370{392. Springer, 2008, and Agustina Buccella, Alejandra Cechich, and Pablo R. Fillottrani. Ontology-driven geographic information integration: A survey of current approaches. Computers and Geosciences, 35(4):710{723, 2009. 38 See Albrecht, Jochen, Derman, Brandon, Ramasubramanian, and Laxmi. Geoontology tools: The missing link. Transactions in GIS, 12(4):409{424, 2008, and Eva Klien and Florian Probst. Requirements for geospatial ontology engineering. In 8th Conference on Geographic Information Science (AGILE 2005), pages 251{260. Citeseer, 2005. 39 http://www.w3.org/2003/01/geo/ 40 See http://en.wikipedia.org/wiki/World_Geodetic_System 41 Open Geospatial Consortium Inc. An introduction to georss: A standards based approach for geoenabling rss feeds. White paper, OGC, 2006. Page 23 of 156


D2.2 Social Validation Methodology geospatial objects (lines, rectangles, polygons). In addition, GeoOWL 42 was developed to provide a more flexible model for geospatial concepts. Furthermore, topological modelling of geometric shapes in RDF can be done with the NeoGeo Geometry Ontology 43. However, all these ontologies only supported WGS84, and currently offer limited support for geospatial operations required in real world GIS workloads. GeoSPARQL has emerged as a promising standard from OGC for geospatial RDF, with the aim of standardising geospatial RDF data insertion and query. GeoSPARQL provides various conformance classes concerning its implementation of advanced reasoning capabilities (e.g. quantitative reasoning), as well as several sets of terminology for topological relationships between geometries. Therefore, different implementations of the GeoSPARQL specification are possible, depending on the respective domain/application. In addition, GeoSPARQL closely follows existing standards from OGC for geospatial data, to facilitate spatial indexing from relational databases.

1.7 Open Data Support 44 SDI4Apps will work with and use the recommendations of Open Data Support, which is a 36 month project of the European Commission to improve the visibility and facilitate the access to datasets published on local and national open data portals in order to increase their re-use within and across borders. Open Data Support is a pan-European initiative targeting both those data publishers that are well underway but also the ones that are just starting (such as SDI4Apps). To achieve its objective, Open Data Support provides to (potential) publishers of open datasets, three types of services to local, regional and/or national public administrations publishing open data: •

Data and metadata preparation, transformation and publication services that will enable them to share the metadata of their datasets on the pan-European linked metadata infrastructure delivered by the project; o The common metadata vocabulary that they are using for describing datasets, is the DCAT Application Profile (DCAT-AP) for data portals in Europe, which is a standard that many EU Member States are considering to adopt 45. o The metadata harvesting and publishing platform that OpenDataSupport is using for collecting metadata of datasets from government data portals, transforming it into RDF, harmonising it according to the DCAT-AP, and publishing it as Linked Open Government Data (LOGD) is based on the Linked Open Data Management Suite developed in the LOD2 project 46 . DCAT-AP includes a number of relevant features, such as how to specify the spatial coverage of a dataset, and work has been undertaken on the use of DCAT-AP

42GeoOWL. http://www.w3.org/2005/Incubator/geo/XGR-geo-20071023/ 43 NeoGeo Geometry Ontology. http://geovocab.org/geometry.html 44 www.opendatasupport.eu - Open Data Support is funded under SMART 2012/0107 ‘Lot 2: Provision of services for the Publication, Access and Reuse of Open Public Data across the European Union, through existing open data portals’(Contract No. 30-CE-0530965/00-17). 45 https://joinup.ec.europa.eu/asset/dcat_application_profile/asset_release/dcat-applicationprofile-data-portals-europe-final#download-linksl SDI4Apps will need to combine and/or transform this approach with spatial data metadata which is described according ISO19115/19119 standards in the INSPIRE profiles. 46 https://github.com/nvdk/lodms-core/tree/virtuoso Page 24 of 156


D2.2 Social Validation Methodology for INSPIRE metadata and automatic transformation from the ISO XML to RDF. •

Training services in the area of (linked) open data, aiming to build both theoretical and technical capacity to EU public administrations, in particular to favour the uptake of linked open data technologies, with a catalogue of online training and tests in order to further knowledge in the field of Open Data Support. o The training curriculum around LOGD that they have developed, which focuses on different aspects, e.g. rationale and benefits, data and metadata quality and licencing, as well as technical aspects of publishing data as LOGD. It comprises 10 self-contained training modules in 3 languages (English, French and German) 47.

•

IT advisory and consultancy services in the areas of linked open data technologies, data and metadata licensing, and business aspects and externalities of (linked) open data.

The project is summarized in the following figure.

Figure 5 Open Data Support services With the aim of advancing the Commission's strategy to promote the data-driven economy 48 and open data policy by accompanying the adoption process of the revised Directive on the re-use of Public Sector Information by Parliament and Council and by promoting open data policies across the European Union. In this vein, the Commission is funding Open Data Support to create the basis for pan-European portals for open data, along with other initiatives such as GEOSS, INSPIRE and Copernicus.

47 It is available under an CC-BY licence at training.opendatasupport.eu 48 The Commission has a strategy to promote the data-driven economy in the EU. This is a response to the European Council's call, in October 2013, for EU action to provide the right framework conditions for a single market for big data and cloud computing. The Communication describes the features of the data-driven economy, including cloud computing, and sets out operational conclusions to support and accelerate the transition towards it. The text of the Communication and Staff Working Document (https://ec.europa.eu/digital-agenda/en/news/communication-datadriven-economy), see also http://europa.eu/rapid/press-release_IP-14-769_en.htm, Memo http://europa.eu/rapid/press-release_MEMO-14-455_en.htm , " The EU strategy on the data-driven economy" https://ec.europa.eu/digital-agenda/en/towards-thriving-data-driven-economy, "What big data can do for you?" https://ec.europa.eu/digital-agenda/en/news/helping-smes-fish-bigdata-ocean and “Helping SMEs fish the Big Data ocean" http://cordis.europa.eu/result/story/rcn/13077_en.html Page 25 of 156


D2.2 Social Validation Methodology The problem that Open Data Support is dealing with is the limited accessibility and the lack of (cross-border) awareness of open datasets published on national, regional and local data portals of European Member States. This has a negative impact on the reuse of these datasets, which remains quite low – certainly beyond expectations. OpenDataSupport has identified the following benefits of using linked data 49 a) Allows for flexible integration of datasets from different sources, without needing the data to be moved. b) Fosters the reuse of information from reference/authoritative sources. c) Caters for assigning common identifiers in the form of HTTP URIs to things (e.g. people, products, business, locations...). d) Provides context to data – richer and more expressive data. e) The use of standard Web interfaces (such as HTTP and SPARQL) can simplify the use of data for machines. But OpenDataSupport also identifies the following considerations for publishing Linked Data that the SDI4Apps platform will need to address: 1. Linked Data is high-quality data. Considerable data cleansing and curation is required. 2. Managing the data lifecycle is a challenging task. Mechanisms for handling updates and deletions in the data should be devised. 3. The tools and software supporting linked data solutions are still not at production level/quality. 4. A central authority should take the responsibility of publishing and maintaining persistent HTTP URIs for data resources. Existing identifiers should be reused to the extent possible, especially the ones coming from reference data sources, such as the INSPIRE Registry 50 , EU Publications Office Metadata Registry (MDR) 51 , and company registers 52. 5. Data is currently available under different licences and in most cases no licence actually exists. This hampers data reuse and integration. Possible licensing options for data and description metadata should be explored. The use of open licence, e.g. a public domain licence – CC0, is recommended, particularly for the metadata. 6. Alternative business model for publishing linked data should be further explored. The costs and benefits of the different alternatives need to identified, before governments can decide on the adoption of the linked data technological paradigm.

49 50 51 52

See http://www.slideshare.net/OpenDataSupport/introduction-to-linked-data-23402165 At https://inspire-registry.jrc.ec.europa.eu/ http://publications.europa.eu/mdr/ See for instance http://opencorporates.com as an excellent open source of such information. Page 26 of 156



2. SOCIAL VALIDATION SDI4Apps uses an user-driven approach towards the development and definition of SDI/Open Data (OD) and metadata models and the user apps that they enable, which consists in starting from the concrete service scenarios in which that information is required and the communities that participate in service delivery as users, providers, or both. This methodology relies on interactive social validation as the keystone to a “demand-pull” approach to defining the SDI4Apps platform functionality and components in a methodology called Social Spaces for Research and Innovation (SSRI), which extends the user-driven Living Lab model 53 beyond the domain of research and into the arena of service deployment 54. A key feature of the SSRI approach is that the processes of service design and user acceptance are not sequential but parallel processes that follow an iterative development path in a constant dialogue between users and service developers and between bottom-up and top-down standpoints. This guarantees, even more than the qualities intrinsic to the service itself, widespread uptake because it is the users themselves who have modelled the service to fit their concrete daily needs, and is totally in line with the emerging Single Information Space in Europe for the Environment (SISE) 55. To achieve the goal of social validation, or to define, establish and implement the process leading to the attainment of social validity, the key issue is to contextualise and streamline a number of methodological references borrowed from other disciplines, taking into account the specifics, the levels of heterogeneity and the needs for simplicity of the six validation pilots in WP6. In that respect, the external validation that will be undertaken later in the project is located at a higher conceptual level then the earlier internal process that will be focused on the effectiveness of the participatory processes in validating the SDI4Apss platform, while the former looks at the general, “behavioural” impact and adoption of the SDI4Apps solutions. Social Validation (or Social proof, also known as informational social influence) is a psychological phenomenon where people assume the actions of others in an attempt to reflect correct behaviour for a given situation. This effect is prominent in ambiguous social situations where people are unable to determine the appropriate mode of behaviour, and is driven by the assumption that surrounding people possess more knowledge about the situation. The effects of social influence can be seen in the tendency of large groups to conform to choices which may be either correct or mistaken, a phenomenon sometimes referred to as herd behaviour. Although social proof reflects a rational motive to take into account the information possessed by others, formal analysis shows that it can cause people to converge too quickly upon a single choice, so that decisions of even large groups of individuals may be grounded in very little information (so called information cascades) 56. 53

As per the Living Lab Helsinki manifesto of 2006, available at www.google.ie/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0CCoQFjAA&url =http%3A%2F%2Felivinglab.org%2Ffiles%2FHelsinki_Manifesto_201106.pdf&ei=CfJwU6LnFsOv7Abf8oC YDw&usg=AFQjCNEXvJYJTyf-_yLw5twcD9feG166ag&bvm=bv.66330100,d.ZGU 54 See “Methodological Framework for Social Spaces for Research and Innovation, Francisco PérezTrejo Senior Adviser, FAO, Sep10, at http://www.aalforum.eu/wp-content/uploads/2013/04/239FranciscoPerezTrejo.pdf 55 See http://inspire-forum.jrc.ec.europa.eu/pg/groups/10035/single-information-space-ineurope-for-environment-sise/ 56 http://en.wikipedia.org/wiki/Social_validation Page 27 of 156


D2.2 Social Validation Methodology This is a risk that will be kept constantly in mind during the SDI4Apps social validation processes 57. The underlying and unifying vision of the SDI4Apps social validation process is the one defined in the HABITATS project 58 to describe the AS-IS (and the TO-BE) situation of each SDI4Apps pilot at the intersection of three main axes – or “impact drivers”: - The level of SDI/LOD in terms of data and metadata models, standards and application schemes. - The extent to which new services and Apps have been developed – or upgraded – using the SDi4Apps platform and tools. - The degree of end-user satisfaction – however this is defined and measured – regarding those services. Generally speaking, we can expect a positive correlation in all pilots, between service development and user satisfaction, which can be quite easy to interpret: in fact, keeping in mind that correlation does not mean causation, it can either be that more and better services are developed to meet the desires and expectation of the end users, or vice versa, that user satisfaction increases after the provision of additional quality services. Whatever the case might be, it should be demonstrated that all of the pilots have followed the direction stated at the beginning of the project, to integrate the user dimension in the process of service and datasets harmonisation and co-creation. In the early evaluative rounds that will be carried out within the SDI4Apps project, “social validation” as the global answer to this question, is related to the benefits associated with the deeper involvement of actual end-users in data access and service co-creation, according to the Living Labs user-centred open-innovation approach 59 . In a conceptual definition of the social validation “space”, the proposed focus of application for behavioural analysis is threefold, namely: A. The social significance of stated goals. • Do the specific development objectives correspond to what users really want? • Are they fulfilling a need that is shared by the prospective end users? • Does the broader community in which the SDI4Apps infrastructure is located value the new services as important to them? B. The social appropriateness of followed procedures. • Do the ends justify the means? • Do users feel that they have a voice in SDI4Apps infrastructure improvement? • How do they feel they are included in the development, implementation and assessment process? • Do users and/or local stakeholders consider the procedures for their involvement acceptable? • Do they recommend them in other situations? C. The social importance of obtained effects. • Are end users satisfied with all of the results, including any unpredicted ones? 57 Using evidence-based social validation rather than preconceived ideas, as advocated in “Think like a Freak” by Levitt & Dubner, 2014, see http://freakonomics.com/books/think-like-a-freak 58 As described in HABITATS deliverable D2.4.2 Impact Assessment, May 2012, available at http://www.inspiredhabitats.eu/index.php?option=com_docman&task=doc_download&gid=12&Itemi d=82 59 http://en.wikipedia.org/wiki/Living_lab Page 28 of 156



Do domain experts value the effects and believe that they were indeed caused (or facilitated) by services developed using the SDI4Apps platform? Does the broader community appreciate the outcomes? Does it value them as something that should be extended to other domains?

Basically we look at what happened, and ask “Did it matter?”.

2.1 Social Spaces & Social Validation The Living Labs methodology consists of a problem driven approach, with short cycles of experimentation, and target communities involvement in the early process. The European Network of Living Labs ENoLL 60 has the following definition “A Living Lab is both a methodology for User Driven Innovation (UDI) and the organizations that primarily use it”. In order to clearly set the Living labs concept in terms of openness, mature level or design approaches the C@R 61 project set the preliminary concept of SSRI with a wider scope considering also the territory and well balanced stakeholders adopting Public Private Partnership (PPP) strategies for sustainable growth. As defined in the HABITATS project 62, Social Spaces for Research and Innovation (SSRI) 63 are defined as organizational ecosystems in which the research and innovation activities are guided by the necessities and constraints of the social communities that benefit from the results, involving, in a balanced way, all of the actors present in the research and innovation value chain such as social communities, technology and solution suppliers, service suppliers, funding organizations and members of the local, regional and national legal, economic and political scene. SSRIs are linked to a specific context or territory whose main pillars or foundations are society, market, policy, technology and infrastructure, shown as follows:

60 www.enoll.org 61 H. Schaffers, J. García Guzman, C. Merz, M. Navarro , Living Labs for Rural Development: Results from the C@R Integrated Project. TRAGSA and FAO Editors. Madrid. 2009. ISBN: 9788469300404 62 HABITATS D2.4.1 Impact Assessment, May 2012, available at http://www.inspiredhabitats.eu/index.php?option=com_docman&task=doc_download&gid=12&Itemi d=82 63 www.researchspaces.eu Page 29 of 156


D2.2 Social Validation Methodology Figure 6 SSRI 5 elements: policy, market, society, infrastructures and technology

2.1.1

Social Validation

This concept pursues the creation of innovation territorial clusters for demand driven open innovation in environmental scenarios. Through enabling new ways of collaboration within sectors, based on ICT solutions, this approach strengthens traditional entrepreneurial activities as well as societal services, and stimulates emerging business activities with the purpose of generating employment and income, reducing costs, improving work userexperience and making marginalised settings more attractive to business activities, venture capital and qualified professionals from elsewhere. SSRI can pave the way from basic research to innovation and facilitates technology transfer to society, including societal pilots and market pilots as market trials. SSRI can guarantee results and societal adoption of the main outcomes of innovation into a profitable approach. It includes all types of testing in available infrastructures, from early prototyping to end deployment. The following diagram maps living labs, test beds and other experimental approaches in the context Technology Readiness Levels (TRL) as defined in General Annex G of the Horizon 2020 work programme 64;

Figure 7 SSRI mapping of TRLs & Testing based on Openness, Maturity & grade of Design. 65

64 As defined in the Horizon 2020 Annex G: TRL 1 – basic principles observed, TRL 2 – technology concept formulated, TRL 3 – experimental proof of concept, TRL 4 – technology validated in lab, TRL 5 – technology validated in relevant environment (industrially relevant environment in the case of key enabling technologies). TRL 6 – technology demonstrated in relevant environment (industrially relevant environment in the case of key enabling technologies). TRL 7 – system prototype demonstration in operational environment, TRL 8 – system complete and qualified, TRL 9 – actual system proven in operational environment (competitive manufacturing in the case of key enabling technologies; or in space. Originally defined in TECHNOLOGY READINESS LEVELS A White Paper April 6, 1995 John C. Mankins Advanced Concepts Office Office of Space Access and Technology NASA. 65 Figure adapted from Ballon, P., Pierson, J., Delaere, S. Fostering Innovation in Networked Communications: Test and Experimentation Platforms for Broadband Systems. Simon Heilesen & Page 30 of 156


D2.2 Social Validation Methodology It can be seen in this figure that early user involvement at stage 0 is an early social validation, followed by a prototyping phase, test-bed, field trials, social validation again, and market pilots in a short iterative cycle. The left side of the figure corresponds to a lower maturity level of technology and in-house R&D, and the right side to a more mature readiness level and real environment validation. The positioning of the SDI4Apps outputs now and as a result of the project are in the spectrum from ‘idea to application’, or from ‘lab to market’, i.e. TRL4 to TRL7. SSRI has become an important instrument for the empowerment of society, promoting new models of governance and relationships between society, national institutions and companies, democratizing the process for innovation. Most approaches do not consider sustainability indicators, lessons learnt and best practices to launch new innovation ecosystems. However SSRI also considers success indicators, quality and maturity measures, clear target communities involved and enough critical mass or representativeness to be considered a strong innovation ecosystem. In line with the European approaches to diversity and different speeds of integration, the SDI4Apps approach to GI/LOD apps recognizes the different characteristics, requirements and goals in the various selected scenarios and countries as well as the highly different initial settings in terms of ICT infrastructure, GI/LOD awareness, existing IT solutions and stages of community building at the start of the project. In some pilot settings, as described in section 5, the project is starting from scratch, in others there is a more mature situation. The methodology framework considers local community building as a basis for end-user engagement, getting key stakeholders involved and agreeing with them about the open innovation strategy, establishing short experimentation, monitoring and evaluation cycles of solutions, and gradually building a policy framework to develop strategies for achieving SDI4Apps enabled Apps’ impact at local, national and European levels. Key messages of state-of-the-art ICT and approaches to open data and PPP will be promoted by the SDI4Apps consortium. Within SDI4Apps the SSRI concept has been adopted as local innovation ecosystems, working with stakeholders and acting as mechanisms for sociotechnical innovation and change although the WP6 pilots will be focused on prototyping and social validation trials mainly. The pilots that will be launched and operated using the SDI4Apps platform will demonstrate the work that must be done to realize the promise of social empowerment and effective adoption everywhere. A main issue is to mobilize the local constituencies including the citizens, and create engagement of all. SSRI stresses the dimension of social innovation and local communities’ engagement. The SSRI concept aims to accelerate the progress of those communities or areas willing to be the ones playing a leading role in their own future and willing to actively participate in the co-creation and design of innovative services and ways of cooperation, generating social welfare and wealth, avoiding at the same time exclusion due to territory singularities. Therefore the SSRI concept will play a relevant role in future projects related to environment, INSPIRE and open data involving the same SDI4Apps pilots.

Sisse Siggaard Jensen, eds (2007) Designing for Networked Communications: Strategies and Development. Hersey: Idea Group Publishing, pp. 137-167. 6 H. Schaffers, J. García Guzman, C. Merz, M. Navarro , Living Labs for Rural Development: Results from the C@R Integrated Project. TRAGSA and FAO Editors. Madrid. 2009. ISBN: 978-84-693-0040-4, as shown in “INSPIRE and Social Empowerment for Environmental Sustainability - Results from the HABITATS project”, 2013, ISBN13; 978-84-616-3646-4 available at www.inspiredhabitats.eu/index.php?option=com_content&view=article&id=86&Itemid=119 Page 31 of 156


D2.2 Social Validation Methodology The HABITATS project observed 66 that normally projects, SMEs, industries, large number of municipalities and public entities interested in wealth creation and improving the citizen’s quality of life do not sufficiently exchange information and do not network adequately, thus lacking a common strategy to exploit synergies for achieving sustainability and societal impact. This goal will be pursued in WP8 (Dissemination and Business Planning) to help ensure active communities or “Social Spaces for Research and Innovation” are created. The real power of SSRI lies in its member’s strengths and its cooperation capabilities in terms of knowledge exchange, joint design and planning of strategies and services oriented to achieve significant improvements, benefits and development of the inhabitants they represent. Public administrations therefore should be able to promote the initial creation and cooperation among national and European SSRI, but also will play their own part in achieving the objectives of regional development.

2.2 Social Validation success

criteria

and

indicators

of

With the above provisions, the objective of the SDI4Apps Social Validation is first of all to identify criteria and indicators of success according to the different standpoints of the actors represented in each usage scenario, as a framework for evaluating the added value of the services that conform to the standards proposed by SDI4Apps. This activity does not start from scratch, but takes into account the taxonomy of social validation approaches elaborated in the HABITATS project 67, i.e.: •

Validation driven by the prospect of user engagement In this case end-users are not yet directly involved in social validation, but the prospect of user engagement is already influencing institutional behaviour.

•

Validation through direct user interaction with the open data access process With the direct participation of (expert/non expert) users in data access.

•

Validation driven by the co-design of innovative “demand pull” services This is the most user-driven approach, as it actually involves final end-users in the co-design of services that use the SDI4Apps platform.

The indicator sets that will be defined will be matched with a composite list of evaluative questions to be used for the pragmatic assessment of impact generated by the Apps and services enabled by the SDI4Apps platform on each of the six pilot scenarios – and more broadly, on the environmental related activities users are involved in. The following table shows a broad initial estimate of the mapping of the 6 SDI4Apps Pilots from the structured descriptions of the User Scenarios in section 5: Pilot & Validation approaches. 1. Easy Data Access 2. Open Smart Tourist Data 3. Open Sensor Network

Validation driven by the prospect of user engagement

Validation through direct user interaction with the open data access process

Validation driven by the co-design of innovative “demand pull” services

X X

X X X

X X

66

In “INSPIRE and Social Empowerment for Environmental Sustainability - Results from the HABITATS project”, 2013, ISBN-13; 978-84-616-3646-4 available at www.inspiredhabitats.eu/index.php?option=com_content&view=article&id=86&Itemid=119 67 Described in “INSPIRE and Social Empowerment for Environmental Sustainability - Results from the HABITATS project”, 2013, ISBN-13; 978-84-616-3646-4 available at http://www.inspiredhabitats.eu/index.php?option=com_content&view=article&id=86&Itemid=119 Page 32 of 156


D2.2 Social Validation Methodology 4. Open Land Use Map through VGI. 5. Open INSPIRE4Youth/ education 6. Ecosystem Services Evaluation.

X X

X X

Table 2 SDI4Apps Pilots & Validation Approaches Social validity refers to the social significance of goals, the social appropriateness of the procedures followed to attain those goals, and the social importance of the effects produced by a given intervention, project or programme 68. In the specific focus area of SDI4Apps, social validity refers to the usage scenarios developed at the level of the six validation pilots in cooperation with the local stakeholders. Social validation is the process of engaging users in the assessment of social validity as a design, implementation, or evaluation attribute in different spheres of research, development and innovation. Social validation deals with three fundamental questions: 1. What should we change? 2. How should we change it? 3. How could we know it has been effective? In the specific focus area of SDI4Apps, social validation can be driven by the prospect of user engagement, occurring through direct user interaction with the open data access process, or manifesting itself in the co-design of innovative “demand pull” services. 69 The significance of SDI4Apps at the pilot level relies on the following: - Validity goes hand-in-hand with quality of the findings. The trustworthy acceptance of the findings relies on their validation. - Social validation embraces therefore assessing the social importance of the effects of any practice, standard or any other issue that is to be central to the project. Validation is thus based on concepts such as reliability and practicability. SDI4Apps will be addressing reliability to the extent to which the validation pilots and their communities are considered to be a true reflection of the reality. Implementation is the practicability of the work, which will also determine, to a large extent, the validity of the process. In other words, social validation will have its building block on a true implementation of the Living Labs approach and methodological framework. Consistent with the above definitions, by impact is meant the ‘influence’ of SDI4Apps thematic innovation on individual actors’ behaviour - including end-users, developers, content providers and policy makers – as well as each of the pilot communities and the population as a whole. Thus, impact assessment broadly covers the enhancement of individual lifestyle and wellbeing as well as the ultimate effects of change on society, the economy and culture. Evaluation is not the same as impact assessment.

Evaluation is concerned with the appraisal of short-term effects of a development, intervention or project. Mainly it refers to whether some verifiable indicators have been met. Evaluation takes place with reference to a number of target beneficiaries and deals with the immediate consequences of change for them.

•

Conversely, the impact of interventions is more complex to assess as it is about lasting change. Impact assessment must go beyond the short, immediate period of

68 Vincent T. Francisco & Frances D. Butterfoss (2007), “Social Validation of Goals, Procedures, and Effects in Public Health”. Health Promotion Practice Vol. 8, No. 2, pp. 128-133, and Montrose M. Wolf (1978), “Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart”. Journal of Applied Behavior Analysis, Vol. 11, No.2, pp. 203-214. 69 HABITATS deliverable D2.4.2 Impact Assessment, May 2012, available at http://www.inspiredhabitats.eu/index.php?option=com_docman&task=doc_download&gid=12&Itemi d=82 Page 33 of 156


D2.2 Social Validation Methodology implementation, as it should seek to understand whether the project continues to influence the process-users-behaviours-institutions-communities afterwards. Thus, another challenge of SDI4Apps is that the timeframe of implementation is short compared to what is needed for the benefits to emerge. In light of the above, SDI4Apps builds on the HABITATS innovative implementation of the SSRI approach applied to impact assessment within the process of social validation – or as an in-built component of the same. To this end, a dynamic/interactive process for user engagement is decisive to: • Contribute to the definition of typologies, roles and responsibilities of stakeholders in the domains affected by the SDI4Apps Platform. • Verify and validate requirements. • Manage requirements by creating baselines and controlling changes. • Understand how to define and improve the requirements of related processes as proposed by SDI4Apps. It is in this way that the SDI4Apps platform will be socially validated and the potential of the services and Apps that it enables will be assessed in each identified usage scenario, illustrated as follows:

Component of Interactive feedback Living Lab assessment of requirements and expected impact

SDI4Apps’ contribution to Social Validation of its GI/LOD platform. Figure 8 Living Lab approach to impact assessment within the process of social validation The following definitions will be used In the remainder of this section:

70 71

-

Internal Validation Pilot = A representation of a context, where user needs are described in terms of expectations and desired functionalities in a general fashion, so as to accommodate several possible scenarios 70.

-

Usage Scenario = An orchestrated, instantiated, setting, comprising all technology and data aspects associated with a given pilot, and related to a specific, possible implementation supported by technological solutions within the context of an experimental deployment. 71

See for instance the 6 pilots described in section 5. These are further described in section 5.1. Page 34 of 156


D2.2 Social Validation Methodology -

Use Case = A descriptive representation of user behaviour, within the context of a possible scenario, allowing the formulation of specific requirements gathering questions or to derive them from predefined user profiles.

To a large extent each Use Case specification will depend on the nature and configuration of Usage Scenarios, which in turn are associated with the WP6 Internal Validation Pilots as plausible test-beds for verifying the hypotheses that each Use Case brings along. This, however, could lead to an excessive proliferation of activities. The Use Cases are organised in such a way that the assumptions at the basis of each Usage Scenario can be readily validated in a qualitative and quantitative fashion with a reasonable amount of effort and time by the relevant project partners. To clarify the meaning of a Use Case compared to a Usage Scenario, examples of Use Cases may include: 1) map browsing on the Internet and via mobile phone; 2) self-definition of the composition of maps based on personal specific interests, and 3) the possibility of uploading information to the server via smart and mobile phones, while section 5.1 describes Usage Scenarios. In the perspective of social validation, the SDI4Apps approach does not consider a Use Case description as a simple instantiation of a Usage Scenario for the sake of development work planning and system testing. Here, the theoretically relevant linkage between a Use Case and a Usage Scenario is (comparatively) less application driven and more (meta)data, ontology, standards and API- dependent than in traditional computer systems analysis. Put it differently, the technical conditions related to any Use Case deployment in the context of SDI4Apps Pilots are not (only or necessarily) examined with respect to proper design and functioning of the enabling SDI or system(s), but particularly in their use of the SDi4Apps Platform tools, facilities and data harmonisation. This affects, of course, the very selection of the Use Cases to be analysed, being on the whole more service and data oriented and less technology driven (also in light of the fact, that evaluation focuses more on the triad “goals/procedures/effects” than “accessibility/usability/interaction” and that the enabling systems at pilot level are yet to be developed/deployed later in the project). An additional, and final, characteristic of the SDI4Apps social validation approach is that normally the users themselves can also propose and support additional Use Cases. This is done by means of a set of evaluative questions that are presented to them before, during or after the SDI4Apps enabled services and apps usage, which in turn contribute to the structuring of user preferences in association to each Validation Pilot. To enable collection of more structured information regarding each Use Case, the structured approach developed in the SmartOpenData project will be used. This collects information using templates for the following 72: • Use Case • Dataset • Application The details of these templates are shown in Annex B.

2.3 Future prospects and scaling-up This section has aimed to describe a process that is staged by necessity, and also highly interactive at each of the proposed stages, illustrated as follows:

72

Described in SmartOpenData, D2.2 “User Requirements and Use Cases”, April 2014, available at www.smartopendata.eu/public-deliverables Page 35 of 156



Figure 9 Social Validation ‘ideal types’ in SDI4Apps 73 According to the evidence at hand, all of the individual pilots may be positioned at a given stage of this process, namely: •

Validation driven by the prospect of user engagement In this case end-users are not yet directly involved in social validation, but the prospect of user engagement is already influencing institutional behaviour. Pilots involved are: 1.Easy Data Access, 2.Open Smart Tourist Data, 4.Open Land Use Map through VGI, and 5.Open INSPIRE4Youth/ education

•

Validation through direct user interaction with the data access process In this case there is, or will be, direct participation of (expert/non expert) users in data harmonisation and access. Pilots involved are: 1.Easy Data Access, 2.Open Smart Tourist Data, 3.Open Sensor Network and 6.Ecosystem Services Evaluation.

•

Validation driven by the co-design of innovative “demand pull” services This is the most user-driven approach, as it actually involves final end-users in the co-design of services that use the SDI4Apps platform. Pilots involved are: 1.Easy Data Access, 2.Open Smart Tourist Data and 5.Open INSPIRE4Youth/ education

Although the main arrow in the figure indicates evolutionary growth, there is also the possibility for a given pilot community to grow and evolve, once it has been properly established, which means that the first stage in the process is more or less common to all – to “skip” the interim stage and go straight to the third one. This is the case, for example, of the “Easy Data Access” pilot, where the first and foremost driver of change is – paradoxically, given the embryonic level of the underlying SDI and SDI4Apps platform – the possibility of co-creating a number of added value services directly with the service and 73 Adapted from HABITATS D2.4.1 Impact Assessment, May 2012, available at http://www.inspiredhabitats.eu/index.php?option=com_docman&task=doc_download&gid=12&Itemi d=82 Page 36 of 156


D2.2 Social Validation Methodology data providers. But even at the first stage, as in the “Open INSPIRE4Youth/ education” pilot, for instance, relevant and meaningful feedback as a guideline for action can be fruitfully gathered. This gradually shifts the attention from the simple collection of user feedback to the value that this may have for the service and Apps owner and the way it can be processed and ultimately taken on-board. In summary, SDI4Apps should contribute to a new strategic approach in the use of its cloud based Platform. The SDI4Apps’ pilots will most likely prove in real cases at the validation pilot sites that there is a large gap between what is required and what is needed. The bottle-necks will probably coincide with those found in previous work, where sound knowledge based on timely, accurate, easily accessed geospatial and environmental information, remains one of the main obstacles in terms of sharing information across European institutions, national agencies, local jurisdictions and stakeholders. To conclude, any SDI/LOD platform should be seen as an evolving concept that sustains (or mediates) various perspectives or stakeholder views. Depending on the user’s interest and role within the broader community, its design and implementation (as well as the corresponding assessment process) gets reshaped by a continuous negotiation and renegotiation with all involved actors. In addition, ‘space’ – or the ultimate object of any SDI/LOD Platform – is socially produced as well, which makes the validating role of sociotechnical platforms such as that of SDI4Apps even more important.

Page 37 of 156



3. METHODS FOR MULTI-STAKEHOLDER ANALYSIS FOR INTERNAL & EXTERNAL COMMUNITIES The methodology for multi-stakeholder analysis adopted for implementation in the SDI4Apps social validation builds on the tradition of community-based participatory research74, asking a number of evaluative questions to assess how involved end-users and more generally the overall population are affected by a given intervention, project or programme. Another key methodological reference point is constituted by the Living Labs/SSRI (Social Spaces for Research and Innovation) 75 approach adopted in SDI4Apps, aiming to deal with the social, organisational and institutional dimensions of innovation alongside the technical aspects, and to engage in validation activities with all user groups, stakeholders, and content providers in an open and inclusive way, supported by the SDI4Apps platform and tools. The consortium considers that one relevant aspect of its focus on social validation is to consolidate SDI4Apps’ added value, in terms of: • Creating a coherent approach to impact assessment as an in-built component for every pilot • Profiling key stakeholders in each pilot • Mapping the policy process, key agents and linkages • Defining dimensions and requirements, such as the content-based aspects of the SDI4Apps platform’s technical functions in addressing data themes such as: – Informatics (meta-data, access, applications), – Syntax (communicating and exchanging data between systems), – Semantics (cultural or institutional interpretation), – To also address social aspects (aggregate social dynamics). Task implementation will move from a detailed consideration of the structural diversities among the SDI4Apps pilot descriptions and communities, which in turn suggests the use of different sets of evaluative questions while keeping the commonalities at the more general/generic level of the multi-stakeholder model. Before engaging into an in-built impact assessment exercise, some common issues have been identified that need to be taken into account, and which are highlighted on the top of the heterogeneity of the validation pilots: • Uncertainty - Many facts may not be known at the validation pilots. • Complexity - One has to consider many interrelated factors, which will unfold as the interface with stakeholders increase. • High-risk consequences - The impact of the decisions on how to approach and develop the underlying communities and other stakeholders may lead to limiting consequences in the development of the enabling environment offered by the Living Lab approach. • Alternatives for development and implementation - Each has its own set of uncertainties and consequences.

74 Vincent T. Francisco & Frances D. Butterfoss (2007), “Social Validation of Goals, Procedures, and Effects in Public Health”. Health Promotion Practice Vol. 8, No. 2, pp. 128-133 75 See http://www.c-rural.eu/index.php?option=com_content&task=view&id=74&Itemid=2 Page 38 of 156


D2.2 Social Validation Methodology •

Relational issues emerging from stakeholders - From the outset, it can be difficult to predict how institutions and groups will react and evolve.

With these difficulties in mind, the best way to conduct a validation or impact assessment of the SDI4Apps platform is to engage into the use of tools (grid analysis 76 , paired comparative analysis 77) that can ensure an effective process. Clear processes usually lead to consistent, high-quality results, and they can improve the quality of almost everything we do. In this context, we have developed a process that will help improve the quality of our outcomes in terms of impact assessment for the social validation aspects of the SDI4Apps project. The project’s impact assessment is carried out in tandem with the community–building work of WP2 as a two-cycle process. •

First cycle: work at the validation pilots with the initiating role of partners responsible for the pilots being pivotal for the organization of the first round of workshops with local key stakeholders.

•

Second cycle: based on a richly-interactive phase, where the involvement of endusers and stakeholders will generate feedbacks that stir the whole process at the pilot level. Component 1

Component 3

Identifying critical factors by partners

First assessment of requirements and expected impact

Interactive feedback:

Component 2

First workshop with stakeholders

criteria for evaluation of potential impact by partners Component 3

First assessment of requirements & expected impact

Figure 10 SDI4Apps Impact assessment process Thus interactive meetings are proposed as an initial tool to support the establishment of a base line for the stakeholders ‘views’ at each validation pilot. The meetings will include clear and simple questions aiming to increase our insight in a structured manner. The overall aim of is to address issues such as: • Who (Would I/we) would benefit from this project? • How would (I/we) benefit from the project?

76 See for instance http://www.mindtools.com/pages/article/newTED_03.htm 77 See for instance http://www.mindtools.com/pages/article/newTED_02.htm Page 39 of 156


D2.2 Social Validation Methodology • •

What should be done to ensure that potential beneficiaries have the opportunity to engage in this process? Would my vision be achieved if sharing and coordinating mechanisms are identified and developed?

Annex C presents an outline agenda for such user meetings or workshops. It is envisaged that these will be customised by the relevant partners to the specific context and requirements for each of their meetings, based on the reporting requirements of the deliverables indicated in Annex C. This locally contextualised approach holds close to the social significance of the goals, the social appropriateness of the procedures, and in determining the levels of behaviour and their reliability as representative of the local needs and of the communities at large.

3.1 SDI4Apps Stakeholders and User Groups Mapping of stakeholders and their interactions provides the basis for the analysis of the potential for market development of the different scenarios as thrown up by the pilots. Different pilots have their own dynamics in terms of the following elements: • Their positioning with respect to the three impact scenarios defined in section 2. • The set of stakeholders involved in developing the pilot requirements and scenarios • The role of the project partner responsible for the pilot within that stakeholder community In addition, while the stakeholder mapping emphasizes the institutional/market relationships between the stakeholders driving their transactions, it is also necessary to model the technical level at which the pilot is operating and the different layers of services involved. The stakeholder and layered service models adopted in SDI4Apps have been developed in the ICT-ENSURE (ICT for Environmental Sustainability Research) project 78, which explored the broad dynamics of the contribution of ICT towards environmental sustainability, considering GIS and INSPIRE an important component.

3.1.1

SDI4Apps Stakeholder roles

The first stakeholder mapping, based on ICT-ENSURE’s analysis of the environmental research problem space, is based on institutional, operational, and economic standpoints related to the environment, and is as follows:

78 www.ict-ensure.eu/en/index.html Page 40 of 156


D2.2 Social Validation Methodology Figure 11 The ICT-ENSURE stakeholder mapping. The key roles identified are: •

Governments and policy-makers: mainly as funders of environmental research, the initiators of top-down actions such as SISE, SEIS, ENHIS, etc., and generally institutionally mandated for the implementation of INSPIRE and open data standards. In SDI4Apps, different levels of government are represented in all of the pilot communities.

•

Environmental experts: experts in the field of the environment (generally Universities or government bodies) applying GI and LOD to improve their capacity to monitor and predict; these actors generally assume an observational stance with respect to the environment, and are also present in several but not all of the SDI4Apps pilots

•

ICT and sector industries: this includes in the broadest sense industrial activities with an effect on the environment, i.e. tourist organisations, agro-food multinationals, the construction industry, etc.; these stakeholders are present in several but not all of the SDI4Apps pilots. This category also includes the ICT industry and its potential interest (low so far, and of particular interest to SDI4Apps) in adopting and building its services on top of the SDI4Apps platform. A good number of SDI4Apps partners therefore fall into this category.

•

Multi-disciplinary research: this groups socio-economic and ICT researchers into a multi-disciplinary perspective on the SDI4Apps problem space as a question of sustainable development including both the environment and human communities within it; this group drives some of the SDI4Apps pilots, particularly those with a stronger Living Lab approach.

•

Stakeholder communities: these are the associations, local NGOs, etc. who represent those directly affected by environmental change; they are involved primarily in information management, dissemination and awareness activities; these actors can be said to be “inside” the environment rather than observing it and are often the “champions” within SDI4Apps pilot communities.

As a general approximation SDI4Apps pilots can be said to be driven by an interaction between the different standpoints represented, so the role played by the SDI4Apps partners driving the pilot actions, as well as the stakeholders chosen to engage in pilot activities, becomes of the utmost importance. An alternative process visualization of the added value of each of the pilots is provided as the following schema 79 (Service and Business Modelling):

79

From Ramon Casadesus – Masanell and Joan E. Ricart (2011) How to Design a Winning Business Model. Harvard Business Review. Page 41 of 156



Involvement

Stakeholder

Interest

Benefits

Stakeholder

Activity

Indirect benefit

Stakeholder

Involvement

Interest

Figure 12 SDI4Apps Pilots Added Value Schema

3.1.2

SDI4Apps User Groups

The SDI4Apps platform will be focused on various users groups:

3.1.3

•

Experts dealing with land use (including risk management) who will use the framework and collected data for their advanced analyses and data processing and also for publication and promotion of their research and other activities.

•

Public (citizens, educators, NGOs...) that will have an opportunity to find new and interesting information about marginal European regions. They will also have a chance to publish their data and participate in decision making.

•

Businesses and SMEs in regions with cultural landscapes. They will use the framework to support their business activities connected with tourism, transport or health care.

•

Policy makers, including local and regional authorities, protected areas administrations, national heritage institutions or environment protection institutions and EC DGs.

User Engagement

User engagement is a key factor to get real impact. In order to promote it, SDI4Apps will set up and maintain a stakeholders group that will provide a frequent feedback from early in the project, establishing a customer discovery process that will allow solutions to be built that really fit the needs of the end users (public bodies, companies, researchers, citizens) of the infrastructure and services. In order to achieve the potential impact of SDI4Apps, several crucial steps have to be taken. Besides the ambitious technical aspects of the realisation of the services and user interfaces, data harmonisation, processing and analysis components, the following issues have to be addressed as well:

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D2.2 Social Validation Methodology (1) First, to ensure that the SDI4Apps platform meets the actual and potential developing future needs of the targeted diverse user communities. It is of central importance to involve members of those as early as possible in the research and development process of the platform. User feedback will be used in turn to adapt and extend the proposed service levels, interfaces, license models and the customisable analysis and processing facilities as needed. See Annex C. (2) As a side effect, the involvement of the community in the first step serves as a starting point for the second step of promoting the platform and its benefits over currently existing offerings and practices to the communities. (3) The second step also provides a basis for the third step that is to gather an initial set of data from various European countries and the development of schema and data format mappings to integrate these data sets and thus actually provide useable content for the platform. This is intended to take place as early as possible right after the basic functionality of the SDI4Apps platform has been integrated. The early availability of the platform to users will amplify the effort made to obtain feedback, data sets and mapping schemas. (4) The fourth step is to verify the actual resource requirements of the SDI4Apps platform to improve the estimated future amounts of traffic and computing power that will be required as the numbers of users, data and custom processing and analysis conducted on the platform increase. This will aid in providing a stable environment with highly-reliable planning data sets which is a critical factor for user acceptance.

3.1.4

SDI4Apps Communities

As described in the DoW, task T2.1 is building the SDI4Apps communities in two iterative cycles. •

•

The first one, initiated at the project’s start-up, builds the core SDI4Apps community around the shared objective of providing the initial state-of-the-art baseline and user requirements It is expected that the first core “active” community will consist mainly of local stakeholders involved in the internal validation. The second cycle will begin when the whole new range of use scenarios will be triggered. It is expected that the unique opportunity of directly participating in shaping these processes and thereby helping to define the open SDI4Apps platform will attract a critical mass of participants and stakeholders to the SDI4Apps community space. As the community grows, the multi-sectoral and interdisciplinary nature of the participating actors adds even further to the added value of co-designing future use scenarios and standards that support them, leveraging a viral multiplier effect for community participation.

In the final months of the project, the SDI4Apps community will be gradually re-structured as a permanent learning community space “owned” by the community itself, with the primary aim of facilitating the diffusion and exploitation of project results through the adoption of the proposed metadata profiles, data models and interoperability standards in all participating stakeholder organisations. SSSA (the leader of T2.1) has identified the following SWOT of the SDI4Apps platform in the context of managing its communities, at this early stage in the project’s development 80:

80

Presented at the sDI4Apps Project Meeting in Jelgava, 17th September 2014. Page 43 of 156


D2.2 Social Validation Methodology Strengths • • • • • •

Weaknesses

The Idea: Technology as a service The technical solution: open API for data integration Utility (Value provided to the users): Free and easy access to data, tools and … A bottom-up approach A learning network for developers Socially responsible investments

Opportunities •

• •

•

•

Explicit shared value The multi-sectoral and interdisciplinary nature of the participating actors is an opportunity. Build deep levels of engagement in the network (user-driven approach) Build sustainable organizational “rules” (metadata profiles, data models and interoperability standards) = Use Linda Tools!!! HYPER as a Bridge Involve other actors to gain trust and increase awareness (host valuable “brand” events to create meta-communities in a long term perspective: a prototypes incubator?) Keep in mind project sustainability over time: -put the basis to capitalise results: consortium agreements? Contracts? Newco?

Less ‘R’ than ‘D’: this is a technology exploitation project, actually lacking of the technology exploitation plan (architectural components) • (Maybe too) late definition of the business aspects: Business Plan initial version is at month 24 & final version at month 36 • Exploration and exploitation in architecture design are concurrent processes • Technological information and market information flows to be started at the same time (avoid duplications in efforts) Threats •

• •

• •

High risk: who leads innovation? R&D or marketing? Clearly define the service that every component provides to the API architecture Adopt a stage gate process in evaluation and testing Concurrently define business model(s) and business plan

Table 3 SWOT of managing the SDI4Apps Communities Implementation and progress in managing the SDI4Apps Communities will be reported in the Annual Reports on Stakeholders Management (D2.1.1/2/3).

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3.2 SDI4Apps Stakeholders’ Service Layers The following table illustrates the HABITATS project’s layered mapping of stakeholders for ICT services 81 such as those enabled by the SDI4apps Platform. SOCIALISATION

Stances are formed, groups interact, decisions taken that influence others.

INTERACTION

Actors & actions interact in causal linkages influencing process outcomes.

KNOWLEDGE

Information is contextualised into dynamic processes & conditions of relevance

INFORMATION

Metadata & harmonisation applying semantic models is applied & information processed

DATA

Raw data is collected, stored & made available for access.

Figure 13 ICT-ENSURE layered model of ICT relevance This dimension of stakeholder mapping refers to the technical level of ICT relevance, which in the ICT-ENSURE project82, was developed as a layered model from the data level up to the social sphere where environmental information is used, as follows: Network Analysis, eParticipation, Social Networks

Discourse Analysis Learning Environments

INTERACTION

Cooperative Systems Simulation, Modelling Environments

Personalised Information Artificial Intelligence

KNOWLEDGE

Publishing Mobile Services Knowledge Management

HCI, Visualisation, Internet of Things

INFORMATION

Semantic Frameworks Information Management Data Mining

GIS, SDI, OD, LOD, Interoperability

Monitoring & Control Mobile Apps Data Capture & Storage

Internet of Things Web Data Services Sensors & Networks,

SOCIALISATION

DATA

Figure 14 Layered ICT infrastructures and services This model can be directly related to the different levels of social validation with respect to data modelling at one extreme and end-user services at the other. It is useful here to see how the ICT-ENSURE project then associates each layer with relevant ICT infrastructures, services, and research fields that can make a contribution to environmental research. Many of the technologies listed here are in fact adopted and/or explored by SDI4Apps pilots.

81 See HABITATS D2.3.1 State of Art, Scenarios and Requirements, June 2011, available at http://www.inspiredhabitats.eu/index.php?option=com_docman&task=doc_download&gid=4&Itemi d=82 82 www.ict-ensure.eu/en/index.html Page 45 of 156


D2.2 Social Validation Methodology With specific relevance to the SDI4Apps project and the focus of this deliverable, the same layers can finally be developed as supporting different levels of the SDI4Apps platformbased services, from the data access level to community and social networking services. SOCIALISATION

SDI4Apps enabled Community Services

INTERACTION

SDI4Apps enabled individual Apps.

KNOWLEDGE

Publishing & Visualisation Tools

INFORMATION

SDI4Apps enabled SDI/LOD Architecture

DATA

SDI4Apps enabled Open Data Models

Figure 15 SDI4Apps-based infrastructure and service layers. To this end, the following list of questions are relevant to the social validation of the SDI4Apps pilots (especially in user workshops later in the project, to elaborate on the agenda shown in Annex C): 1. Status of Community Building and Engagement • Conceptual basics for the social validation: creating a critical mass of multistakeholder partnerships (different mechanisms within SDI4Apps: creation of local social networks/participating in other networks…) • Current status (including local social network groups) • What do they wish to see and to contribute to in the social networks? • What do stakeholders appreciate and recommend in terms of dissemination/awareness-raising and other mechanisms for user engagement? 2. Face-to-face Involvement process: Workshops  Rationale for SDI4Apps at the pilot level  Living Lab Approach (LLA) status of mainstreaming at the pilots  Advantages associated with the co-design of services targeted to user’s requirements  Potential on-line and off-line services of the SDI4Apps enabled services  Discussion on current trends in technology  What is at stake: technology accessible to regions  The interlinks amongst the local/regional/national contexts  Best/good practices in technological advances  Bottlenecks of the process in technical/operational terms  How the current policy environment enables or restricts standardization & adoption  Identification of these policies - at what scale: local/regional/national/EU?  How can SDI4Apps support better decision-making? 3. Impact Assessment  What are the expected benefits of the SDI4Apps platform for your organisation?  What do you think are the platform’s benefits for the community?  And how about the combined benefits with SDI4Apps in the pilot?  Identified gaps in the wide application of the different technological advances in GI and LOD. How have impacts been assessed? Page 46 of 156


D2.2 Social Validation Methodology         

Innovation in terms of joint accountability of coordination/integration: codesigning evaluation of impact In your opinion, how useful is the social validation? What should be the criteria for evaluating the impact of SDI4Apps in the pilot? How to quantify and qualify it? Resulting benefits from feedback as part of the social validation: expectation of best case scenario What are the ‘enabling’ elements of better decision-making? What decision and policy framework and level of governance can be addressed by the integration of services/sharing data, etc. Expected impact from the overall project? How will SDI4Apps matter and make a difference ?

4. Additional contents (optional):  Twinning opportunities for the pilots. o Potential for twinning/sustainability and up-scaling issues o What mechanisms to develop for this?

3.3 SME Capacity building To build capacity amongst European SMEs and to guarantee participation of local stakeholders and users, to support building of stakeholders group and support new developers, the project will widely disseminate the SDI4Apps results in WP8 (Dissemination and Business Planning), including the following activities: 1. Promote capacity building, dissemination and exploitation of results of SDI4Apps with other organizations of geospatial world (SME, public, private, academic and NGO’s) 2. Facilitate dialogue between scientists, policy makers and civil society, letting the voice of the final users be heard. 3. Provide, in collaboration with SMEs, developments of new open source applications. 4. Establish an international partnership, with initiatives such as OSGeo, EUROGI, EFITA, OGC, ISOCARP and Are3NA. 5. Participate in scientific meetings and outreach. 6. Produce scientific publications. 7. Strengthen collaborative networking between partners, for activities related to "community building" and "dissemination and exploitation". 8. Develop user-friendly online services for primary data-holders in their data publication and management. 9. Increase the level of awareness, interest and knowledge about the SDI4Apps platform. 10. Organise two contests for best applications using SDI4Apps. 11. Support SME developers and freelancers in their development using the SDI4Apps platform. 12. Organise workshops and sprint codes at pan European conferences. 13. Define Open Source based licensing policy for geospatial extension of SDI4Apps. 14. Define business model for future sustainability of SDI4Apps platform. The SDI4Apps team will be focused on building a community of companies and users to build a Living Lab type of virtual organisation. There will be further target groups, where organisation will be invited, such as: • Open Source GIS community. • Organisations dealing with INSPIRE implementation, with GEOSS, GMESS and UNSDI. • GIS developers from other areas such as risk management and agriculture.

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D2.2 Social Validation Methodology This will build on the experience of the Living Lab approach, especially as the Czech partners are members of Czech Living Lab Member for ENNOL. The team will also offer infrastructure to existing and future research projects in the area of GEOSS and GMES. As part of the creation of a dynamic innovation ecosystem, a contest for developers will be organised in cooperation with APPS4Europe activities (supporting Open Data Access), where partner CCSS is a member. The SDI4Apps market and community will include, not just organisations working with the public sector, but also organisations building applications focused on citizens. Cloud integration of public data and VGI could also build a new environment. In this regard, collaboration with different voluntary and Open Data initiatives such as OpenStreetMap and GEO-WIKI will be important.

3.4 SDI4Apps Multistakeholder Evaluation Process SDI4Apps’ innovation is grounded on the Living Labs/SSRI approach to address the challenges of impact assessment. The process that will be used builds on an assessment study of the Living Labs “phenomenon”, promoted by the European Commission in 2008 83, where an updated version of the MASAI approach 84 was developed and implemented, focusing on the transition phase of European Living Labs from R&D towards industrially and commercially viable solutions. •

At the top level of the process, the project partners (possibly including local stakeholders) will define a set of usage scenarios (A, B, … N) related to the implementation of services and Apps enabled by SDI4Apps in the communities. To each scenario, duly instantiated in terms of data availability, metadata, data models and application schemes, a number of success indicators is preliminarily associated, expressing the supposed impact on individual and/or collective conditions.

•

At the lowest level of the process, actual and prospective end-users are expected to introduce their own requirements by way of self-profiling themselves (or as an alternative, by selecting one out of several predefined “profiles” of usage). To each individual profile (either custom or preselected) a number of evaluative questions are associated, which depend on the ideal type of social validation (see Table 1) and produce a list of concrete, operational, scenario-related use cases..

The above aims to engage in evaluation those actors who actually use (or will use in the future) the data harmonising/sharing, services and services derived from use of the SDI4Apps platform in their daily work, for decision-making, or simply betterment of their own lives. The involvement of current and newly engaged end-users is assumed to be the driving force for the permanent adoption of the platform, while the user communities are to grow and actively upgrade and maintain content as well as innovate. Finally, the communities themselves will validate the concrete usage and its derived benefits. The social evaluation process relies on the initial identification of usage scenarios done by the stakeholders and partners located at the validation pilots. However, we expect that new possibilities of usage will be generated out of the interaction with the platform of the 83

Study on the potential of the Living Labs approach, including its relation to experimental facilities for future Internet related technologies. Final report. Brussels: European Commission, 2008. 84 The MASAI basic approach has first been developed by MTA in 2004 and used for a Study of the Impact of the IST Programme, and of its predecessor Programmes Esprit IV, ACTS, TAP (Contract N° C28262 with DG INFSO). Page 48 of 156


D2.2 Social Validation Methodology pilot community members. This structured and iterative stock-taking exercise will also contribute to the potential scaling-up of SDI4Apps findings and tools, including the engagement of a higher number of participants and better definition of sustainability of user’s involvement, later in the project. The analysis of the comparability and compatibility areas for the expected twinning of pilots 85 will also be furthered. In order to capture the overall work of SDI4Apps the following evaluative steps will be followed in sequence: 1. First to present the four key questions listed earlier in this subsection 3.2 to each pilot owner. 2. Then appoint a pilot evaluator acknowledged by the entire consortium; 3. The WP2 leader (VPR) in periodically ask each pilot site, which will be used submitted to the European

close coordination with the leader of WP6 (ZPR) will owner for a written description of the situation at each to prepare several (public or restricted) deliverables Commission (as indicated in the Annex C);

4. The SDI4Apps consortium project meetings will be profitably used as the forum to agree on the way forward. The leader of WP2, in close coordination with WP6, will lead dedicated sessions during these face-to-face technical meetings. These will be preceded by preparatory work and followed by telephone/Skype conferences. The aim of this interactive process will be to discuss the collected views/comments and documents where several partners will be offering advice, making suggestions and promoting an approach to the potential interoperability of individual pilots with others in the project. 5. The preparatory work for the final conference of SDI4Apps (D8.6) will be dedicated to a search for commonalities between pilots and to leveraging the unique contributions received from some of the pilots in order to define a replicable and sustainable strategy to improve the services through stakeholder cooperation and better use/promotion of the SDI4Apps platform. In general, it should serve to develop a common understanding and more conceptual clarity of achieved project outcomes. The SDI4Apps social validation process will report on the lessons learnt in each of the six pilots by adopting the following common structure for all of them: o Community Building and Engagement o Emerging Business Models o Added Value of the SDI4Apps platform o Interoperability with other SDI4Apps Pilots The precise implementation and monitoring of this multistakeholder evaluation process, and in particular the interaction between the Tasks and Pilots, will be elaborated and reported in the Internal Validation Reports (D2.3.1/2/3).

85 See HABITATS deliverable D2.4.2 Impact Assessment, May 2012, available at http://www.inspiredhabitats.eu/index.php?option=com_docman&task=doc_download&gid=12&Itemi d=82. Page 49 of 156



4. SUSTAINABLE OPERATION OF THE SDI4APPS FRAMEWORK A key objective of the SDI4Apps project is the sustainable operation of the SDI4Apps platform after the project ends, to ensure the long-term sustainability of the SDI4Apps data toolsand network services, and exploitation of project results by guaranteeing added value and return on investment to the different stakeholders involved. As explained in the DoW, SDI4Apps is building on a well-established platform that has been steadily developing over the years with several similar projects, culminating in the HABITATS, Plan4Business and EnviroGRIDS services. SDI4Apps is now integrating GI and LOD advanced tool sets, and combining them with local experience of participatory processes in the global context. The focus is on turning existing SDIs into regular businesses. WP8 (Dissemination and Business Planning) is focused on moving the SDI4Apps platform into real business, by: o stimulating local ICT businesses (networked across regions /countries /continents); o attending to large corporate business (aim: making powerful allies and providing them with tools/knowledge to make their operations sustainable, locally and globally). Community-based businesses foster trust, commitment, high-quality of products and services, accountability, social-environmental responsibility, business ethics, and “contagious commitment”. So in each of the 6 pilots of WP6, the project will nurture the Service Provider and User concept and make them both integral to the participatory process so that it will become accepted as a necessary interchange and form part of an emerging business environment. It is envisaged that the robust stakeholder involvement central to SDI4Apps will not only generate sustainable economic returns through the interface between the business and the scientific community, but will guarantee a solid contribution to a knowledge-driven economy. Long-term sustainable implementation of the SDi4Apps platform will depend on three main pillars. 1. The first is a large user community with strong commitment (based on involvement, trust and the benefits they receive from using the services) (WP2, WP7). 2. The second is a reliable supply of global SDI data content, guaranteed large scale services (WP5). 3. The third is a thriving private sector of small enterprises (individuals, SMEs and NGOs) that provide value-added services of mutual benefit to all involved (WP7, WP8). SDI4Apps will stimulate networking of organisations dealing with SDI for environment (regions, NGO, universities, high schools, life long education). Implementing the project at European level enables the consortium to cover the complete chain and allow know-how, experience, methodologies, and general practice to disseminate throughout Europe. The networking capacity of SDI4Apps will be increased as many of the project partners are members of international bodies, and they are able to use this network to extend the impact of the project. In addition, both the awareness and training activities of the project (such as the local workshops and sprint codes) as well as the exploitation and sustainability activities (such as the partner affiliation networks of planners, universities, content publishers, and professional/planning associations) will promote the uptake of

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D2.2 Social Validation Methodology results from interested stakeholders, and invited interested organisations to join the project by joining the SDI4Apps communities. SDI4Apps will have a significant networking capacity built into each of its partners, and will capitalize on this asset to achieve the required critical mass for building the SDI4Apps social networking communities to the point where it is a dynamic and self-sustaining social space that accompanies and extends the reach of SDI4Apps results. SDI4Apps will develop tools that allow users to integrate and where needed semantically annotate the data from various tables, OGC services and Linked Data sources in the system. State of the art semantic web technologies will be used to support: a) data integration in the backend area, b) data enrichment in the form of linked (open) data consumption from the Linked Open Data (LOD) clouds and/or from additional open data sources, and c) powerful semantic search mechanisms and additional publishing mechanisms to enable use and re-use in the frontend area. In addition, the vision of SDI4Apps is to work towards the development of a system of systems relying on enabling a dynamic understanding and monitoring of the environmental and climatic spheres, and the complex interactions between physical and social environment. From a business point of view, many SDI applications suffer from lack of flexibility in the underlying IT and communication infrastructure. While “cloud” providers address some aspects of this problem, today’s ICT technology can neither assure the end-to-end quality of service, nor can it meet the customers’ specific requirements on privacy and confidentiality of information.

4.1 Long term viability of SDI4Apps As a project that aims to develop and promote the adoption of the SDI4Apps Platform, the long-term viability of SDI4Apps depends on the systemic sustainability of three main elements: 1. The adoption and spread of the proposed SDI4Apps data harmonisation tools, metadata models and network services, their maintenance and further development 2. The sustainability of the stakeholder partnerships that participate in the validation pilots and therefore constitute the foundations of SDI4Apps scenarios, and the growth of similar partnerships across Europe. 3. The growth and continued vivacity of the SDI4Apps communities as spaces for the socialisation of innovation and promotion processes. For the first element concerning interoperability and harmonisation processes, the SDI4Apps consortium is confident that the user-driven methodology adopted throughout the project is the best guarantee of ensuring long-term viability of the SDI4Apps platform and that the scope and nature of the validation pilots constitutes the ideal mix for sparking of its viral adoption. The second element touches on an important innovation in SDI4Apps, namely the service delivery model for the setting up and delivery of the validation pilot services. This model broadens the PPP (Public-Private-Partnership) and “triple helix” (PPP plus University) approaches to the kind of multi-stakeholder local partnership that characterises the Living Lab and SSRI approaches. The social validation activities in SDI4Apps are intended to enhance the pilot evaluation approaches with a better understanding of these partnerships and their dynamics as a means of ensuring that the roles of different stakeholders and the perceived benefits are sufficient to guarantee the long-term viability of the partnership and the services it delivers. Page 51 of 156


D2.2 Social Validation Methodology The third element is therefore strongly linked to this ecosystem concept, since SDI4Apps social network is where this ecosystem lives and will be made manifest. criteria for long-term viability here are not economic or institutional, but rather continued social vitality generating a return on participation for each members of communities involved.

the The the the

WP8 (Dissemination and Business Plan) will pay careful attention to each of these dynamics later in the project, and recognize that not one service or business model or plan could fit the variety of stakeholders in the project partnership and in the SDI4Apps communities. Although the main emphasis is on the formalization of multi-stakeholder models and agreements to facilitate the dynamics of sustainability, it is appreciated that the project partnership as a whole would find the stipulation of a long-term agreement a useful tool to ensure the long-term viability of the services that the project developed over its lifespan, even though these services may only be the core nucleus of an ecosystem of SDI4Apps services developed on their own, and that will develop in the future. The broader socio-economic context of the long-term viability of SDI4Apps will be explored in WP8 using a Territorial Innovation model which has been developed to underpin the notion of a Territorial Living Lab 86. In this model, the typologies of actors involved are the same as in the traditional concertation and participation processes in spatial and strategic planning, and correspond roughly to the participants and communities in the SDI4Apps pilots. These are classified according to political decision-makers, technical experts in the various fields concerned (not only ICT) and the citizens and businesses that make up the socio-economic fabric of the territory, and their interactions as shown in the following diagram:

Figure 16 Territorial Innovation Interactions Territorial Innovation occurs in the overlap, where the roles of all three of the actor groups come together, and also where all three of the interaction processes – the formation of Territorial Capital, the political commitment of actors, and the articulation of the innovation demand – overlap. As each of the 6 validation pilots evolve they will continue to rely on trans-regional and trans-European data sharing between pilot settings, within networks of interest present in the project and with collaborating members of the SDI4Apps user communities.

86

Marsh, J.2008: Living Labs and Territorial Innovation. In: Collaboration and the Knowledge Economy: Issues, Applications, Case Studies, IOS Press, Amsterdam (NL), 2008. Page 52 of 156



4.1.1

Future Challenges

SDI4Apps will identify the models to define the roles and responsibilities of different typologies of actors involved in the SDI4Apps platform enabled services scenarios, as well as the sustainability and exploitation plans for each pilot and agreement among partners for the long-term management of the SDI4Apps outcomes. Ultimately, the involvement of final end users from the outset in the processes of designing and validating the GI/LOD SDI4Apps platform is what drives its adoption process itself and thus the best guarantee of continued upgrading and maintenance of the content represented. A key objective of the project is sustainable operation of the SDI4Apps platform and its enabled services after the project ends, to ensure the long-term sustainability of the SDI4Apps data harmonisation tools and network services and exploitation of project results by guaranteeing added value and return on investment to the different stakeholders involved. Experience from the SDI4Apps pilots to date clearly indicate that mobile platforms will play an important role in INSPIRE adoption, as the usefulness of accessing certified geographical data for an increasing range of applications emerges. These provide major exploitation opportunities for all of the pilots, and the INSPIRE community must also take notice and collaborate directly with developers of mobile apps for application in location-based services. The phone apps under experimentation in the SDI4Apps pilots will highlight the ability of a mobile app to access local data in the same way in any locality across Europe. LOD and INSPIRE compliant systems can also offer this possibility, while offering significantly richer local geographical information that is certified by public authorities. Smartphone apps provide users with a wider range of engaging experiences, social networks and mobile operating systems have opened their platforms to developers, transforming the creation, distribution and consumption of digital content. This is leading to an “App Economy” 87. In the App Economy, developers can create applications accessing unique features of the platform; distribute applications digitally to a broad audience and regularly update existing applications. The App Economy is much more than a better delivery channel for software. From the economic perspective, the App Economy can be viewed as a collection of interlocking innovative ecosystems. Each ecosystem consists of a core company, which creates and maintains a platform and an app marketplace, plus small and large companies that produce apps and/or mobile devices for that platform. Businesses can belong to multiple ecosystems and usually do. Every major consumer-facing company and many business-facing organisations have discovered that they need an app to be their public face. In some sense, that makes the App Economy the construction sector of the 21st century, building a new front door to everyone’s business and in some cases constructing a whole new business opportunity. Europe 2020 is the EU’s growth strategy for the coming decade. The impact of the apps economy on EU’s growth is going to be even higher than what it is already today. The impact on new jobs creation is expected to be very relevant. The apps economy will also have an impact on a more efficient use of resources for a sustainable growth. Eventually, the apps economy will allow for an easy link of the whole EU society to the digital world 88. The Digital Agenda for Europe (DAE) calls for the Commission to reinforce the activities bringing together stakeholders around common research agendas. In particular, DAE action 54 aims at working with stakeholders to develop a new generation of web-based

87 See for instance www.visionmobile.com/ blog/2012/08/theriseofthenewappeconomy and www.cultofmac.com/175065/insidetheappeconomymakingbigmoneyisfarfromasurething 88 See http://ec.europa.eu/europe2020/index_en.htm Page 53 of 156


D2.2 Social Validation Methodology applications and services, including for multilingual content and services, by supporting standards and open platforms through EU-funded programmes 89. Innovation Union (IU) aims at creating more jobs and maintaining EU’s competitiveness on the global market. This goal can be reached by increasing the competitive position of EU businesses and organisations on the apps economy. Innovation Union aims at revolutionizing the way public and private sectors work together, notably through Innovation Partnerships between all stakeholders (the European institutions, national and regional authorities and business). To this aim SDI4Apps has identified a multi-stakeholder local SSRI PPP approach and segment of the App Economy that could have a major impact on the various stakeholders involved 90. There exists many different information sources for protecting the environment in Europe in coastal zones, agricultural areas, forestry, etc., mainly focused on the Natura 2000 network, and areas where activities like agriculture, forestry, tourism need to be balanced with the Habitats Directive and the European Charter for Sustainable Tourism in Protected Areas. Nevertheless, the economic value of these areas is still largely unknown. EU SMEs will define mechanisms for acquiring, adapting and using data provided by existing sources directly involved in biodiversity and environment protection in European protected areas. The SDI4Apps platform will directly help those initiatives to (i) harmonise metadata, (ii) provide spatial data fusion, (iii) improve spatial data visualisation and (iv) publish the resulting information according to user requirements and Linked Open Data principles to provide new opportunities for SMEs. These future projects will reuse existing European SDI, based on INSPIRE and GEOSS (like SDI4Apps, but not only: HABITATS, Plan4all, Plan4business, EnviroGRIDS, Brisedie, GEOSS registries, national INSPIRE portals). The SMEs involved will develop new services based on this data and research on biodiversity. Environmental Agencies and National Parks will benefit by improving their knowledge of their biodiversity, maintenance and protection. Public bodies, researchers, companies and European citizens will take a central role in user-driven pilots developed to enhance the potential of protected areas. Innovation by third party SMEs will be encouraged by the promotion of royalty-free open standards and best practices generated. Open public data resources for reuse are one of the key priorities of the Digital Agenda for Europe. Data available in public European organisations have an enormous potential economic growth. Nevertheless, finding and accessing environmental information isn’t always straightforward 91. The SDI4Apps platform will make spatial data easier to discover and use, having a positive impact on the public and standard availability of data according to the Linked Open Data Strategy for the purpose of environmental information. The new vision derived from the SDI4Apps project is that environmental and geospatial data can be more readily available and reusable. Focusing on Spatial Data, it is possible to use the power of Linked Open Data to foster innovation, economy and increase efficiency in the management of that data.

4.2 Source Licence Model SDI4Apps will follow a licensing model compatible with the exploitation plans of the industrial partners of the consortium. The partners agreed 92 to provide the open reference implementation of the SDI4Apps infrastructure under the Apache-2 licence, as it:

89 See http://ec.europa.eu/information_society/digitalagenda/ index_en.htm 90 See http://ec.europa.eu/research/innovationunion/ index_en.cfm 91 http://inspire.jrc.ec.europa.eu/events/conferences/ inspire_2012/presentations/ray_b.pd 92 At the project Kickoff Meeting on 15-16th April 2014. Page 54 of 156


D2.2 Social Validation Methodology (i) (ii) (iii)

explicitly grants rights where necessary to operate, modify and distribute the software; permits code that it covers to be subsumed into closed source projects; is suitable for safeguarding the IPR of project results as well as EC investments.

Standardisation and open source are key enablers for fostering competition in enabling openness and interoperability across vendors without vendor lock-in concerns. The SDI4Apps partners will preserve their investments and will make their non-open source services compliant with the proposed open source reference implementation, and will continue with proprietary developments, according to their exploitation plans. These developments will provide added-value solutions for the reference implementation. The access to these developments will be granted to the rest of the project partners during the project life, and joint exploitation plans on these developments will be analysed in the project Exploitation Plan that will be developed in WP8.

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5. SDI4APPS USER SCENARIOS The SDI4Apps platform and tools will be socially validated through 6 deployed pilot demonstrators that will be technically evaluated for: (a) the effectiveness of the approach for the Cloud, LOD and semantic services; (b) how well the proposed architecture can be adapted to different scenarios. (c) the limitations and benefits of the approach compared to existing technologies. The social validation begins by the relevant consortium partner defining Use Cases in the User Scenarios of each pilot, in the structured format, described in Annex B, which has been adapted from the SmartOpenData project 93 in line with the methodology described in sections 2 and 3. These structured descriptions will evolve as the project and social validation develops with the communities involved. The evaluation will be provided on the basis of the following 6 pilots (as defined in the DoW): 1. Easy Data Access; 2. Open Smart Tourist Data; 3. Open Sensor Network; 4. Open Land Use Map Through VGI; 5. Open INSPIRE4Youth; 6. Ecosystem Services Evaluation. Direct interoperation between these pilots is expected to be as follows: Pilots P1 P2 P3 P4 P5 P6

P1 X X

P2 X X

X X X

X X X

P3 X X

P4 X X

P5 X X

X X X

X X X

P6 X X X X X X

Table 4 Interoperation between Pilots This is based on the initial structured descriptions of each of the pilot scenarios in sub-sections 5.2 to 5.7. But first we need to define scenarios.

5.1 Scenarios Scenarios describe the stories and context behind why a specific user or user group comes to a service or app. They note the goals and questions to be achieved and sometimes define the possibilities of how the user(s) can achieve them on the site 94. Scenarios are critical both for designing an interface and for usability testing. Good scenarios are concise but answer the following key questions: •

Who is the user? Use the personas that have been developed to reflect the real, major user groups coming to the service.

93

SmartOpenData, D2.2 “User Requirements and Use Cases”, April 2014, available at www.smartopendata.eu/public-deliverables 94 http://www.usability.gov/how-to-and-tools/methods/scenarios.html Page 56 of 156



Why does the user come to the service? Note what motivates the user to come to the service and their expectations upon arrival, if any.

•

What goals does he/she have? Through task analysis, we can better understand what the user wants of the service and therefore what it must have for them to leave satisfied.

•

How can the user achieve their goals using the service? Define how the user can achieve his/ her goal on the service, identifying the various possibilities and any potential barriers.

In the context of the SDI4Apps platform enabled services and apps, a scenario is a narrative, which most commonly describes foreseeable interactions of user roles (known in the Unified Modelling Language (UML) as 'actors') and the technical system, which usually includes computer hardware and software 95. A scenario has a goal, which is usually functional. A scenario describes one way that a system is or is envisaged to be used in the context of activity in a defined time-frame. The time-frame for a scenario could be (for example) a single transaction; a business operation; a day or other period; or the whole operational life of a system. Similarly the scope of a scenario could be (for example) a single system or piece of equipment; an equipped team or department; or an entire organization. Scenarios are frequently used as part of the system development process. They are typically produced by usability or marketing specialists, often working in concert with end users and developers. Scenarios are written in plain language, with minimal technical details, so that stakeholders (designers, usability specialists, programmers, engineers, managers, marketing specialists, etc.) can have a common example which can focus their discussions. Increasingly, scenarios are used directly to define the wanted behaviour of software: replacing or supplementing traditional functional requirements. Scenarios are often defined in use cases, which document alternative and overlapping ways of reaching a goal. Types of scenario in system development Many types of scenario are in use in system development. Alexander and Maiden list the following types 96: •

Story: "a narrated description of a causally connected sequence of events, or of actions taken". Brief User stories are written in the Agile style of software development.

•

Situation, Alternative World: "a projected future situation or snapshot". This meaning is common in planning, but less usual in software development.

•

Simulation: models to explore and animate 'Stories' or 'Situations', to "give precise answers about whether such a scenario could be realized with any plausible design" or "to evaluate the implications of alternative possible worlds or situations".

•

Storyboard: a drawing, or a sequence of drawings, used to describe a user interface or to tell a story. This meaning is common in Human–computer interaction to define what a user will see on a screen.

95 http://en.wikipedia.org/wiki/Scenario_(computing) 96 “Scenarios, Stories, Use Cases: Through the Systems Development Life-Cycle, Ian F. Alexander (Editor), Neil Maiden (Editor), Wiley, ISBN: 978-0-470-86194-3, 548 pages, August 2004 Page 57 of 156



Sequence: a list of interactive steps taken by human or machine agents playing system roles. The many forms of scenario written as sequences of steps include Operational Scenarios, Concepts of Operations, and Test Cases.

•

Structure: any more elaborately-structured representation of a scenario, including Flowcharts, UML/ITU 'Sequence Charts', and especially in software development Use cases.

It is impossible to write down every scenario that every user has for visiting a service. Instead, before starting to put the services site together, its better to write down the most common reasons that users have for visiting or tasks that users want to do. Scenarios can also work together with personas by serving as the stories behind why the particular persona would come to the service or use the App. What does the persona hope to accomplish by visiting the site? What characteristics of the persona might help or hinder his or her site interaction? The focus is on users and their tasks rather than on the service's organization and internal structure. As a result, the content that the service must have and how it should be organized can be determined.

5.1.1

Using Scenarios in Usability Testing

When identifying scenarios for usability testing, the test should involve a limited number of tasks due to time constraints. Additionally, in a usability test, users can be asked for their own scenarios. Why would they come to the service/app? What do they want to do? Usability testing scenarios should not include any information about how to accomplish a task. The usability test will show how the participant accomplishes a task and shows whether the interface facilitates completing the scenario. However, how to accomplish the task should be documented. This information is included in the material that the observers and note-takers will use. Include the main pathway and any alternative pathways the participant may use to accomplish the scenario. After the test, compare how it was thought that users would complete the task to how they actually completed the task. This comparison provides valuable insight into the effectiveness of the web service/app’s architecture and navigation.

5.2 Easy Data Access Pilot This pilot will support easy access to existing services and will integrate an API solution, which will support easy collection of information using smart phones and integrate this information into current SDIs. The pilot will include: • integration of HS-CAT with a Geo‐Focused Crawler - foreseen to be adopted for automatic collection of OGC services endpoints representing spatial content available via deep web (accessible only via specific SDI desktop and client applications). • design and adoption of an Open API which will support easy collection of information using smartphones and integrate this information into existing SDI. • generalise the principles for transfer of such solutions into scalable environments and combine them with the principles of LOD. • evaluation of the effectiveness of the SDI4Apps solution, and limits and benefits of the solution in comparison with existing technologies.

Page 58 of 156



reuse of previous results from the HABITATS and EnviroGRIDS projects. The task will also cooperate with ELF (European Location Framework) 97 , SmartOpenData 98 and Plan4business 99.

More and more mobile apps dealing with spatial data are being adapted. Most of them are based on Google Maps, others using proprietary map engines such as Locus 100 . These applications are using their own proprietary protocols and they are not integrated with current INSPIRE or GMES infrastructures. The intention of the Easy Data Access pilot application is to adapt an Open API which will support easy integration of new applications with existing SDIs. The HS-CAT mobile phone application 101 for searching, browsing and displaying metadata records (ISO 19115 / 19119 / 19139) developed in the HABITATS project, will be used and will be extended by new possibilities of accessing existing INSPIRE services, other data standards and easy use interface. The main features of the beta HS-CAT are it is: • Based on OGC Catalogue Service for the Web (CSW) 2.0.2, ISO application profile 1.0. • Ready to access INSPIRE and other SDI catalogues. • Catalogued Web Map Services (WMS) may be displayed in Locus app. • Catalogued KML may be displayed in Google Maps. The solution will use results of the Irish pilot from SmartOpenData provided by MAC. The pilot will be focused on the wider communities’ identification, reporting, and recording of tourist destinations and ground truthing of Irish protected heritage sites datasets (based on the INSPIRE Protected Sites Data Specification 102) by adapting a phone app and system that involves the wider communities through awareness, using social media, crowdsourcing and open map-based geospatial data. Easy Data Access will generalise its principles, transfer such solutions into scalable environment and combine it with LOD principles. Easy Data Access will be more focused on collecting metadata than on data. Data will be then integrated from distributed sources using OGC services and LOD principles. At the first level the following will be integrated: • different European INSPIRE metadata based catalogues; • other Geospatial catalogues related to GEOSS, Copernicus and other geospatial infrastructures; • catalogues from other EU projects; • metadata of Geospatial services harvested from resources available on Web, but not described in regular catalogues using Metadata Web Crawler; • catalogues of Open non geospatial data and Linked Open Data. All of these metadata resources will be integrated using SuperCat from the HABITATS Reference Laboratory 103 and will be available through HS-CAT. SDI4Apps will exploit mobile phone apps developed in previous projects such as HS-CAT – metadata catalogue for easy access to data and services, as follows: 97 www.elfproject.eu 98 www.smartopendata.eu 99 www.plan4business.eu 100 www.locusmap.eu 101 See www.habitats.cz/hs-cat 102 Defined in http://inspire.ec.europa.eu/documents/Data_Specifications/INSPIRE_DataSpecification_PS_v3.0.pd f 103 www.habitats.cz Page 59 of 156



Figure 17 Catalogue client result list, metadata detail and map portrayal.

5.2.1

Easy Access Scenario 1: Mobile Apps to support Tourism for Conservation

This Pilot Scenario and Use Case in Ireland will be derived from the SmartOpenData 104 project and is described in the format shown in Annex B as follows: Introduction The Burren and Cliffs of Moher is one of UNESCO’s recognised Global Geoparks. Geoparks are special regions with outstanding geology and local culture, with a management structure dedicated to the sustainable development of the region through research and tourism. The Burren and Cliffs of Moher Geopark is about people and organisations working together to ensure a cared-for landscape, a better-understood heritage, more sustainable tourism, a vibrant community and strengthened livelihoods. The Geopark is managed by Clare County Council with funding from the Geological Survey of Ireland and Fáilte Ireland. The Geopark also manages the Burren Tourism for Conservation LIFE Project (LIFE11/IE/922) 105. The aim of this LIFE project is to strengthen the integration of tourism and natural heritage, reconciling tourism development with conservation of geology, biodiversity and cultural heritage in the Burren area of County Clare. The innovative aspect of the Project is to advance tourism for conservation as a European methodology of value to local communities. This aims to be a strong demonstration project with pilot actions being stimulated to test the use of tourism for conservation in the Burren. The Burren and Cliffs of Moher Geopark LIFE project is a 5 year programme (2013 – 2017) of actions which aims to reconcile tourism and conservation in the region. The GeoparkLIFE programme is focused on 3 areas: (i)

Developing sustainable ethos and practices amongst a critical mass of tourism businesses

104 www.smartopendata.eu 105 See www.burren.ie Page 60 of 156


D2.2 Social Validation Methodology (ii)

Demonstrating integrated management practices at a selection of sites and monuments Creating a transferable tool kit for sustainable destination development

(iii)

The project’s main objectives are: 1. To create a transferable model for sustainable tourism destination development built on partnership; and 2. To show measurable environmental, social and economic benefits of the model. The SD4Apps platform enabled apps will directly contribute to the second objective, and be part of the model that can be transferred to all European GeoParks. Use Case ID:

UC.07.01

Use Case Name:

SDI4Apps enabled ETIS Webservice for the Burren & European GeoParks Network

Created By:

John O’Flaherty, MAC

Last Updated By:


Date Created:

12/05/2014

Date Last Updated:

02/09/2014

Actors:

Abstract:

Description:

1. Public bodies – National Parks Wildlife Service (NPWS) 2. Experts – Researchers and management in the Burren GeoPark, GeoParks Network. 3. Enterprises, Companies and SMEs – Burren GeoPark 4. Citizens – visitors to the Burren National Park. The SDI4Apps enabled European Tourism Indicators System (ETIS) webservice for sustainable management at destination level, will streamline and enhance the current manual system by transforming the ETIS Excel dataset into Linked Open Geospatial Data. The Burren Geopark’s solidity as a destination is exemplified by its benchmarking and monitoring procedures. It has adopted the recently launched European Tourism Indicator System for the Sustainable Management of Destinations (ETIS) 106 to monitor and measure performance and is one of 100 destinations in Europe that are currently piloting this system. Further to this, Failte Ireland, the national tourism development authority, has expressed interest in using the Geopark’s work on the ETIS as a pilot for assessing for larger-scale, national projects. The SDI4Apps enabled European Tourism Indicators System (ETIS) webservice for sustainable management at destination level, will streamline and enhance the current manual system by transforming the ETIS Excel dataset into Linked Open Geospatial Data, and enable the Burren GeoPark initially (and all other GeoParks subsequently) to: 1. Set up their destination with suitable indicators and targets (by its Local Destination Co-ordinator and Stakeholder Working Group). 2. Provide online data collection by each stakeholder group

106 http://ec.europa.eu/enterprise/sectors/tourism/sustainable-tourism/indicators/index_en.htm Page 61 of 156


D2.2 Social Validation Methodology (including Destination management, Enterprise , Resident and Visitor Surveys) – this will include automatic updating from appropriate online source databases. 3. Review progress and results achieved to date at their destination by Monitoring Results and Charting Destination, Enterprises, Residents, Visitors Impressions, Spending and Time – this will include automatic geographic visualisation by linking to appropriate Geospatial data sources. This will enable the Stakeholder Working Group and visualisation by the various stakeholders to provide an ongoing community “crowsdsourcing verification” that the results and data being entered matches the perceptions of the various stakeholders. 4. Provide benchmarking with other destinations (e.g. other GeoParks) through each of these views and access to their linked open datasets 107. The webservice will be accessible on PCs, Tablets and Smart Phones. It is anticipated that as each destination’s use of the ETIS matures and the indicator data collected becomes more extensive, the webservice will enable comparisons of the destination’s progress against international benchmarks. This will give greater context to the achievements and give destination stakeholders motivation to take further actions to improve results. It will also encourage knowledge sharing between destinations. The intention is not to create competition between destinations, but to recognise that the results generated through the process are core to the decision making plans for each destination. Preconditions:

EITS Excel standard dataset must be transformed into Linked Open Data and hosted on the SDI4Apps Platform.

Postconditions:

User SDI4Apps platform to include automatic geographic visualisation by linking to appropriate Geospatial data sources and enable benchmarking with other GeoParks in the GeoPark Network.

Name of the Input ETIS standard dataset. Dataset: Name of the Burren ETIS dataset. Output Dataset: Name of Application Front-end Facilities

the Standard HTML5 Browser on PCs, Tablets and Smartphones to access the Webservice. 1. Semantic indexing infrastructure (of Excel/CSV to open RDF) 2. Visualisation framework (of its GI components and progress charts)

107

The pilot may find that the ongoing community stakeholders’ crowdsourcing verification at point 3, may not be adequate for the Geoparks Network, who may prefer to include independent 3rd party verification of the data to ensure the integrity of the ETIS benchmarking across the Geoparks. This may require another visualisation option across the destinations to verify that the data being entered is good as basically the GeoParks will be competing with each other in the GeoParks Network benchmarking exercise. Page 62 of 156



Frequency of Use: Existing Tool:

3. Notification service (to various stakeholders to access the Burren service) Daily during peak tourism season. ETIS dataset and manual process, defined http://ec.europa.eu/enterprise/sectors/tourism/sustainabletourism/indicators/index_en.htm

in

Development Type

Recycle: SDI4Apps has to adapt this webservice from the SmartOpenData project Normal Course of The Burren GeoPark Team will be able to: Events: 1. Set up their destination with suitable indicators and targets (by its Local Destination Co-ordinator and Stakeholder Working Group). 2. Provide online data collection by each stakeholder group (including Destination management, Enterprise, Resident and Visitor Surveys) – this will include automatic updating from appropriate online source databases. 3. Review progress and results achieved to date at their destination by Monitoring Results and Charting Destination, Enterprises, Residents, Visitors Impressions, Spending and Time – this will include automatic geographic visualisation by linking to appropriate Geospatial data sources. This will enable the Stakeholder Working Group and visualisation by the various stakeholders to provide an ongoing community “crowsdsourcing verification” that the results and data being entered matches the perceptions of the various stakeholders. 4. Provide benchmarking with other destinations (e.g. other GeoParks) through each of these views and access to their linked open datasets 108. Once proven by the Burren Team, further GeoParks will be able to implement similar activities, and provide benchmarking with other destinations (e.g. other GeoParks) through each of these views and access to their linked open datasets 109. Exceptions: These will be determined as part of the development of the ETIS webservice. Includes:

Crowdsourcing input of the ETIS dataset values.

Special Requirements:

Crowdsourcing verification of the ETIS dataset values.

108

The pilot may find that the ongoing community stakeholders’ crowdsourcing verification at point 3, may not be adequate for the Geoparks Network, who may prefer to include independent 3rd party verification of the data to ensure the integrity of the ETIS benchmarking across the Geoparks. This may require another visualisation option across the destinations to verify that the data being entered is good as basically the GeoParks will be competing with each other in the GeoParks Network benchmarking exercise. 109 The pilot may find that the ongoing community stakeholders’ crowdsourcing verification at point 3, may not be adequate for the Geoparks Network, who may prefer to include independent 3rd party verification of the data to ensure the integrity of the ETIS benchmarking across the Geoparks. This may require another visualisation option across the destinations to verify that the data being entered is good as basically the GeoParks will be competing with each other in the GeoParks Network benchmarking exerecise. Page 63 of 156


D2.2 Social Validation Methodology User Validation:

Criteria of Success of the Scenario

• • • • • • • • • • •

Interoperation with other SDI4Apps Pilots SDI4Apps Service required

P2 P5 P6

Cloud • Model • •

User Engagement Direct user interaction with open data access processes Co-design of innovative “demand pull” services Usage level & Social Validation of Services that use SDI4Apps Easy collection of information using smart phones & LOD Integration of VGI into existing SDIs & LOD Increased access to harmonised & interoperable GI, L/OD & VGI data Integrate data from users’, OD, crowd-sourced & social media. Reuse & share tourist information resources, channels & tools SMEs, Students & Researchers developing new Apps New tourism activities, visitors & jobs, and SME developed services. - Open Smart Tourist Data - Open INSPIRE4Youth - Ecosystem Services Evaluation Applications – Software as a Service - SaaS Platform as a Service - PaaS Infrastructure as a Service - IaaS

SDI4Apps Enabler • Functions required •

Scalable crowdsourced/VGI real-time data collection with an Open API. Scalable RDF Triple Storage service for the LOD (such as Virtuoso 110) • Scalable GI to LOD transformation and harmonisation service. • Scalable Geo‐focused Crawler for automatic collection of OGC services endpoints representing spatial content available via the deep web. • Semantic indexing infrastructure to transform GI to LOD • Visualisation framework (of GI and non-GI components) That the SDI4Apps platform will be able to provide 5 star CSV linked open data, in line with the W3C “CSV on the Web” WG work 111

Assumptions:

Notes and Issues:

MAC needs to work with the Burren GeoPark Team to refine the interactions and use of the ETIS dataset.

ETIS Dataset Dataset ID:

UC.07.01;DS.01

Dataset Name:

ETIS Dataset

Created By:


Last Updated By:


Date Created:

12/05/2014

Date Last Updated:

11/06/2014

Dataset description:

The European Tourism Indicator System for the Sustainable Management of Destinations (ETIS) 112 to monitor and measure

110 http://en.wikipedia.org/wiki/Virtuoso_Universal_Server 111 See http://www.w3.org/2013/05/lcsv-charter.html Page 64 of 156


D2.2 Social Validation Methodology performance of destinations in Europe. Dataset type:

Excel/CSV transformed into LOD RDF using the SDI4Apps platform.

Availability:

Dataset is currently only available as an offline Excel file.

Format& Storage:

Currently Excel offline. Will be transformed Excel/CSV to LOD RDF by MAC using Enablers of the SDI4Apps Platform. GI inserts in ESRI Shapefile.

Size:

RDF) Storage – on the SDI4Apps platform

128 Ground truthing is the process of gather data in the field that either complements or disputes airborne remote sensing data collected by aerial photography, satellite sidescan radar, or infrared images (http://www.missiongroundtruth.com/groundtruth.html), see also http://en.wikipedia.org/wiki/Ground_truth 129 See www.heritagecouncil.ie 130 http://heritagemaps.biodiversityireland.ie/#/Map 131 Defined in http://inspire.ec.europa.eu/documents/Data_Specifications/INSPIRE_DataSpecification_PS_v3.0.pd f 132 See www.logainm.ie/en/ 133 http://inspire.ec.europa.eu/registry/ Page 71 of 156


D2.2 Social Validation Methodology Description: Access Rights:

• Search • Visualization Dataset license: To be determined in discussions with the Heritage Council, and National Monuments Service. Likely to be Creative Commons Attribution Non-Commercial No Derivatives (CC BY-NC-ND) 134 Is the dataset public? No. Is it free? Yes Allowed Operations: • Read – Yes to all stakeholders with access. • Write – Yes for all stakeholder with access. • Modification – Yes, for National Monuments Service and Heritage Council relevant staff.

Potential Monuments Ground Truthing Application Application ID:

UC.07.02;AI.01

Application Name:

Potential Monuments Ground Truthing Application

Created By:


Last Updated By:


Date Created:

12/05/2014

Date Last Updated:

11/06/2014

Application description:

Responsive HTML5 Browser/App on PCs, Tablets and Smartphones to access the Webservice

Availability:

Does not yet exist.

Format:

• •

Graphical user interface – Standard HTML5 browser. Machine readable interface – simple and light RESTful webservice using JSON to allow App access. Supported Implementing the National Monuments VGI Ground-Truthing process as functionality / indicated above for individual farmers. capabilities: Viewing, searching, editing for the Heritage Council and National Monuments Service staff.

5.3 Open Smart Tourist Data Pilot The rapid growth of tourism and the tourist industry in the 20th century is related to changes in social structure of society and rights of labours. They contributed to the introduction (in developed countries) of weekends, eight-hour working day and holidays, that strongly support tourism activities. Active tourism (contrary to passive tourism) is a special way to spend leisure time. It is a new life philosophy that combines adventure, 134 Creative Commons licenses consist of 4 major condition modules (see http://en.wikipedia.org/wiki/Creative_Commons_licenses) 1. Attribution (BY), requiring attribution to the original author; 2. Share Alike (SA), allowing derivative works under the same or a similar license (later or jurisdiction version); 3. Non-Commercial (NC), requiring the work is not used for commercial purposes; and 4. No Derivative Works (ND), allowing only the original work, without derivatives. Page 72 of 156


D2.2 Social Validation Methodology sports, experience, discovering, events, and relations to nature, history, culture, habits or traditions. Active tourism is rapidly growing in popularity due to an unusual experience that are totally different from the typical in sea resorts. Elements of active tourism (such as excursions or offer of sport activities) are added to the traditional form of tourism. The new forms of tourism cover for example sport activities (e.g. rafting), nature tourism (e.g. trekking or hiking), rural tourism, congress tourism, adventure tourism (e.g. rock climbing) or experience tourism (e.g. mountaineering expeditions). Another shift of paradigm of the tourist industry is in connection with collecting, sharing, spreading and propagation of information. Previous forms (personal recommendations, printed catalogues, reservation letters or phone calls) are in remission and they are replaced by electronic forms. But electronic forms are also changing. They are moving from centralized databases and big global providers to more personalized information created by local subjects of tourist industry. The main objective of this project is to support these local or regional subjects and their information management, because we believe that the combination of local and global information and systems represents the best added value for all participants of the tourist industry. The Open Smart Tourist Data pilot will support related business subjects such as easy integration of the SDi4Apps platform into proprietary solutions (thanks to the implementation of standards), reusing and sharing of existing information resources, channels and tools. Open Smart Tourist Data will integrate users’ data, free and open global data, SDI4Apps Team’s data, crowdsourced data and social media. This pilot application will represent a practical and useful subset from the wide range of outputs of tourist data related projects. It will cover and integrate: • • • • • •

a wide range of input data sets; design and modify processing and exploitation methods and implement standards; improve the presentation of results and communication between participants in the tourist industry; develop and implement business methodologies and procedures; evaluate the effectiveness of the SDI4Apps solution, and limits and benefits of the solution in comparison with existing technologies; reuse of results from the HABITATS project and cooperation with ELF (European Location Framework).

Data and information represents keywords of current society as well as contemporary tourism and the tourist industry. Both are major subjects of the tourist industry (participants and providers) that deal with data and information and need them mainly for communication within each group and also between both groups of tourism subjects. Data and information involve a huge number of varied items related to selection of destination or offer of services of the tourist industry. Data and information do not mean just spatial data sets, maps, web cameras, hand-outs or catalogues, but also personal information such as recommendations, comments on social media channels, published private photos or stories. Existing solutions for the tourist industry based on information technologies (IT) are focused mainly on one component of information such as global information, local or regional data or social media and crowd-sourcing. The main problem of this approach is that various types of information are collected and managed at different levels. For example, it is possible to have a central database of roads on the European level, but it is not possible to maintain up-to-date uniform information about accommodation, services, events, etc. On the other hand, there are local systems, which are collecting this information. These systems usually cover small regions or groups of service providers with up-to-date data, but

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D2.2 Social Validation Methodology the problem of such local information systems is their heterogeneity and usability. All users (including SMEs participating on the tourist industry and being not focused on information technologies) or such data and information are limited by their heterogeneities that cover various data models, data formats, types of information, level of detail, semantics (terminology), portrayal rules, geometry, coordinates and coordinate systems and above all the updating frequency. Travellers have their own requirements. They want to find interesting, attractive and credible information simply and fast without any difficulties. The heterogeneities limit sharing and reuse of existing data sets as well as their integration to external applications and data sets. The heterogeneity means also very important questions related to reliability and quality of the provided information. Two 135

136

FP5 projects ReGeo and EMIRES aimed to build future information systems on the basis of shared information from local levels. Due to technological constraints this idea has not been realised until now. ReGeo introduced the concept of virtual tourist information systems and EMIRES introduced the concept of the Single European Tourist Market Place. Both of these concepts will be modified by SDI4Apps using new technological possibilities and a number of European data providers. The new data component of the tourist industry constitutes Volunteered Geographic Information (VGI) related to crowd-sourcing, e.g. Wikitravel (free, complete, up-to-date and reliable world-wide travel guide; shared repository for images and other media), OpenStreetMap, Open Weather Map or Open Event Map. Open Smart Tourist Data will interconnect user requirements and characteristics of existing data sources. This approach will add other components such as global and local open data sources and crowd-sourcing initiatives (e.g. OpenStreetMap), own data of the partners, social media (to provide another type of information and feedback from real users) and the latest technologies and technological standards that enable to use various hardware platforms and devices to manage, collect and present data.

5.3.1 Smart Tourism Pilot Scenario

Cycle tourism is an important and high growth area. Bicycle touring generally means selfcontained cycling trips over long distances, which prioritize pleasure, adventure and autonomy rather than sport, commuting or exercise. Touring can range from single day rides to multi-day trips, or even years at a time. Tours may be planned and organised by the participant/s for themselves or organised for a group by a professional holiday business, a club, or a charity as a fund-raising venture

137

The Smart Tourism pilot scenario will implement a Smart Cycle Tourism Information service that will intelligently discover and seamlessly combine local, regional and global information sources relevant to cycle tourists, their preferences, current location and planned cycle routes. The service will be piloted on a regional basis in the Czech Republic and Latvia. The proposed service will integrate the following types of data sources:

135 http://www.istworld.org/ProjectDetails.aspx?ProjectId=7a5ee46de82d4f52b7179abc1de3ca2e&SourceDatabaseId=951ef712ec ba4f7ca229527509db4a81 136 http://www.istworld.org/ProjectDetails.aspx?ProjectId=17cc2ae67f914582895728bbde31692c&SourceDatabaseId=951ef712e cba4f7ca229527509db4a81 137 http://en.wikipedia.org/wiki/Bicycle_touring Page 74 of 156


D2.2 Social Validation Methodology 1. Free and open global data (published mainly by state administration or international organizations; e.g. VMAP /Vector Map/ or Urban Atlas). This group will also include statistical data related to the tourist industry (e.g. data from EUROSTAT, World Tourism Organization or World Travel and Tourism Council). This latter will not be as relevant for tourists, but will be mainly for the tourist providers, and destination management (somewhat similar to the ETIS scenario in the Easy Access Pilot). 2. Users' data (e.g. notes and comments of particular visitors and participants; they will be collected using web forms to uniform structure based on common data model; they will represent the most important data source from the point of view individual presentation and acquisition of data), both VGI focused on tourists as well for the tourist providers. 3. Partners' data (added by particular providers of tourist industry, it includes new offers, news or improvements of services). 4. Free and open-source local and regional data (published mainly by local administrations, local non-profit organizations, living labs, local action groups etc.). 5. Crowd-sourced data and Volunteered Geographic Information (including products such as OpenStreetMap, Open Weather Map or Wikitravel). 6. Social media (comments, recommendations and opinions not only from common social media like Facebook, but also from social media focused on tourism, e.g. Trip Advisor, Reveable or WAYN). Users or participants (travellers, visitors) will be able to find information in one place and to compare and evaluate information from different sources. A simple and attractive interface will be implemented. Proposed presentation through static web pages will be based on HTML 5 that is suitable not only for PCs but also for smartphones and tablets with small displays and limited Internet connection. Use Case ID:

UC.03.01

Use Case Name:

Smart Cycle Tourism Information system

Created By:

Otakar Cerba, Karel Last Updated By: Charvat, Tomas Mildorf, Josef Fryml

Otakar Cerba (UWB)

Date Created:

05/07/2014

05/07/2014

Actors:

Abstract:

Date Last Updated:

•

Public bodies – European, National, Regional and Local Authorities providing tourism related information. • Experts – Tourism & Economic development; Regional decision makers. • Enterprises, Companies and SMEs – related to tourism (including accommodation facilities, restaurants, hospitals etc.). • Citizens – visitors and people interested in cycling and their local environment. The Smart Tourism pilot scenario will implement a Smart Cycle Tourism Information service(s) that will intelligently discover and seamlessly combine local, regional and global data and

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D2.2 Social Validation Methodology information resources relevant to cycle tourists, their preferences, current location and planned cycle routes. The service will be piloted on a regional basis in the Czech Republic and Latvia. Description:

The pilot will be closely connected to the activity Cesko jede (ceskojede.cz). Both activities plan to provide information about all forms of motor-less tourism and related services through the web map application. The pilot aims to combine data and information offered by particular regions, providers or local authorities as well as commercial web resources. The application enables accessing of cycling-marketing products according to the target groups (e.g. families with children, sportsmen, bikers, etc.). Users will be able to find and explore a wide knowledge base containing various points of interest, interesting trips, bike rentals, connection to public transport, inline skating, accommodation etc. The application will be based on an unique combination of data stored in pilot storage, harmonized external data (for example E.L.F) (exploited by services or Linked Data principles), VGI data (e.g. OpenStreetMap, Open Weather Map) and user feedback and recommendations. The pilot application will be accessible on PCs, Tablets and Smart Phones. But an API supporting easy integration for external developers, will also be developed. The pilot will follow the majority of existing and arising standards from the field of tourism as well as information technologies (including INSPIRE, Open Geospatial Consortium, World Wide Web Consortium), and emerging tourism vocabularies 138.

Preconditions:

Harmonization of stored data resources Development of links between particular objects in data resources Linking of data connected as Linked Data

Postconditions: Name of Datasets:

the

Existence and updating of connected data Input •

VGI data: OpenStreetMap, Open Weather Map, Wikitravel, etc.

•

E.L.F

•

Thematic data like forest roads (FMI}

•

Data provided by local, regional or state authorities

•

Data provided by commercial subjects involved to tourism (e.g. public transport)

•

Data provided by Cesko jede activity (e.g. link to cycling web pages)

138

See for instance, TourMISLOD: a Tourism Linked Data Set, at http://www.semantic-webjournal.net/content/tourmislod-tourism-linked-data-set Page 76 of 156


D2.2 Social Validation Methodology Name of the Output Smart Cycle Tourism Dataset Dataset: Name of Application

the Smart Cycle Tourist Assistant

Front-end Facilities

•

Semantic indexing infrastructure

•

Visualisation framework

•

Notification service

•

Open API

Frequency of Use:

Daily

Existing Tool:

Particular web pages and web tools designated for cycling tourism (e.g. Cesko jede, Labska stezka, Posazavi, NISA GO etc.).

Development Type:

Development of new application (with use of fitting fragments of various methods such as Living Lab, Open Innovation, Agile Prototyping, Incremental development, Spiral development etc.). Re-using of existing datasets, services and applications.

Normal Events:

Course

of

Exceptions:

1. Users enter the application and select region and areas of interests. 2. System visualizes user requirements. 3. System recommends fitting services and points of interests. 4. Users will able to use analytic functions of the system (e.g. routing). 5. System provides links to other information that will be not embedded into application. 6. Users can export information to their GPS tools, smart phones, printers etc. 7. Users can provide feedback to application developers as well as recommendations to other users. 8. System will offer selected data as Linked Data. These will be determined as part of the development of the Smart Cycle Tourism Information system.

Includes:

-Different crowdsourcing data


-Methods for data verification and validation

User Validation:

• • •

User Engagement Direct user interaction with open data access processes Co-design of innovative “demand pull” services

Criteria of Success of the Scenario

•

Usage level & Social Validation of Services that use SDI4Apps Easy collection of information using smart phones & LOD Increased access to harmonised & interoperable GI, LOD& VGI data Integrate data from users’, OD, crowd-sourced & social media.

• • •

Page 77 of 156



Interoperation with other SDI4Apps Pilots SDI4Apps Cloud Service Model required SDI4Apps Enabler Functions required

Reuse & share tourist information resources, channels & tools • SMEs, Students & Researchers developing new Apps • New tourism activities, visitors & jobs, and SME developed services. P1- Easy Data Access P5 - Open INSPIRE4Youth P6 - Ecosystem Services Evaluation • Applications – Software as a Service – SaaS • Platform as a Service - PaaS • Infrastructure as a Service - IaaS • •

• • • •

•

Scalable crowdsourced/VGI real-time data collection with an Open API. Scalable GI to LD transformation and harmonisation service, from many heterogeneous database sources, including HALE 139 (HUMBOLDT Alignment Editor) support. Scalable RDF Triple Storage service for LD Semantic indexing infrastructure to transform GI to LD Advanced Visualisation framework and API (of GI and nonGI components) Scalable fast PostGIS and concurrent PostgreSQL support, providing clustered real-time updates on all master databases. Scalable intelligent deep-Web GI/LD Search and discovery with an open API

Assumptions:

- That the SDI4Apps platform will be able to provide the required 5 star CSV linked open data, in line with the W3C “CSV on the Web” WG work and will make it accessible through an open API.

Notes and Issues:

-UWB, HSRS, CCSS will work together with Uhlava, ZPR & VPR, but also external partners will be included, such as CDV, Czech Regions. There will be close cooperation with the Irish pilot, mainly through the Burren GeoPark.

Dataset Dataset ID:

UC.03.01;DS.01

Dataset Name:

Smart Cycle Tourism Data

Created By:

Otakar Cerba, Karel Last Updated By: Charvat, Tomas Mildorf, Josef Fryml

Otakar Cerba

Date Created:

05/07/2014

05/07/2014

Dataset description: 139

Date Last Updated:

Various input datasets connected to cycle tourism (resources

https://joinup.ec.europa.eu/software/hale/description Page 78 of 156


D2.2 Social Validation Methodology are described above). It will be distributed database. Dataset type:

Spatial data (GML, SHP, GeoJSON) Descriptive and statistical data HTML web pages Excel and other structured data

Availability:

Availability of fitting datasets will be tested and arranged during the pilot development. Formats (see above)

Format& Storage:

Storage – RDBMS, file systems, web services Size:

The size will cover big data (e.g. OpenStreetMap) as well as small data sets (usually data from particular tourism service providers).VGI data sets coming from providers and tourist will be included.

Openness:

Authors will prefer data provided under an open licence but due mixture of data sources, large heterogeneity of licenses is expected.

LOD Status:

The guarantee of 5* Linked data as well as its maximal implementation will be a priority of the pilot.

LOD Functionality Description:

• Links to similar or equivalent objects • Links to thesauri and controlled vocabularies • Data in an open format (probably RDF) • Metadata Access right will depend mainly on integrated external data.

Access Rights:

Application Application ID:

UC.03.01;AI.01

Application Name:

Smart Cycle Tourist Assistant

Created By:

Otakar Cerba, Last Updated By: Karel Charvat, Tomas Mildorf, Josef Fryml

Otakar Cerba

Date Created:

05/07/2014

05/07/2014

Date Last Updated:


Responsive HTML5 Browser/App Smartphones to access the service

Availability:

Does not yet exist.

on

PCs,

Tablets

and

Format:

• •

Supported functionality / capabilities:

•

Graphical user interface – Standard HTML5 browser. Machine readable interface – simple and light RESTful webservice using JSON to allow App access. Visualization of data

•

Analyses (e.g. routing)

Page 79 of 156



Collecting of feedback and recommendation

5.4 Open Sensor Network Pilot The aim of the Open Sensors Network pilot is to create an environment where different groups of volunteers (for example farmers) will be able to integrate low cost sensors (meteorological, quality of air, etc.) into local and regional web sensor networks. The pilot application will integrate meteorological data and in-situ meteorological sensing networks based on small stations collecting agro-meteorological data to support the crop production systems. The pilot will define a framework for taking advantage of intelligent sensor webs based on the converging technologies of standard meteorological sensors, micro sensors, computers, and wireless telecommunications with data management and analysis in support of agriculture production activities, such as the chemical protection, grape and wine production, fruit protection and production. The knowledge gained from integrated sensors sensing has the potential to empower managers and decision makers to act on crop and fruit production. The importance of meteorology advisory and measures in agriculture has been increasing during the last decades due to the emerging need to access appropriate information as a consequence of the rapid changes on weather conditions. Although the quality of weather forecasting has improved constantly and agriculture is benefiting from this achieved capability, in many European regions, the currently available meteorological data are not sufficient for crop production, as much additional local scale data is needed to be integrated into the specific agro-meteorological models and to take the correct decision in any farm management system. To meet the farmers’ ambitions, especially in the areas where the land parcels are relatively small and involving the growth of “expensive” cultivars (fruits), there is a need of establishing networks of local sensors and meteorological stations. The ongoing significant advancements in sensor technologies and in-situ sensing are expected to support also the development of more systematic capabilities for assimilating all sorts of in-situ measurements in agro-meteorological models, at relevant scales, to generate immediately (in real time) useful information for farmer’s decision making. The data will also be available for the public sector. It will help not only the farmers, but also protection services. Large monitoring networks will be built using neogeography and VGI principles for sensors.

5.4.1

Open Sensor Pilot Scenario

Agriculture requires the collection, storage, sharing and analysis of large quantities of spatially referenced data. For this data to be effectively used, it must be transferred between different hardware, software and organisations. These data flows currently present a hurdle to uptake of precision agriculture as the multitude of data models, formats, interfaces and reference systems in use result in incompatibilities. Management of huge amounts of data is a challenge. Sensors in the fields, buildings, vehicles or satellites provide data on high time-frequency and fast accumulation of data. Without smart sensors and better developed data management (including data quality algorithms) the amount of data grows overwhelming and remains unused. Spatial data quality is considered to consist of several aspects, which may be categorised as data completeness (amount of missing features), Data Precision (positional accuracy or degree of details), Data accuracy (attribute accuracy) and Data Consistency (absence of conflicts of spatial

Page 80 of 156


D2.2 Social Validation Methodology elements). Agricultural data often also has a temporal dimension, thus called spatiotemporal data, consistency in time is also considered. Spatio-temporal data is increasingly collected by remote or in-situ sensors rather than by field campaigns. The wireless communications have several benefits, but also pose challenges to the data exchange reliability and power supply. Sensor calibration and deployment as well as maintenance of sensors need resources and technical skills and increase the costs of data acquisition). Both increasing the amount of data and awareness of data quality issues highlight importance that metadata are attached to sensor data. The Open Sensor Network scenario will integrate: 1. 2. 3. 4.

Partner reference data, which will include farm maps, regional maps etc.; VGI reference data mainly OpenStreetMap and other available data; Publicly available reference data like topography, imageries; Sensors measurements – sensor data measurements coming from different sources such as farms, and schools. 5. Open Meteorological and environmental data - it will include free available data sources.

The pilot will include: • analysis of pilots needs concerning measured parameters and accuracy; • selection of concrete sensors (wireless sensors networks); • deployment of sensor infrastructure; • adopting a QAPP; • plug-in sensor infrastructure into SDI4Apps; • plug-in advanced visualisation tools; • plug-in analytical modules; • provide measurements; • evaluation of the effectiveness of the SDI4Apps solution, and limits and benefits of the solution in comparison to existing technologies; • close cooperation with the FOODIE project140. Use Case ID:

UC.15.01

Use Case Name:

Open Agricultural Sensor Network

Created By:

Karel Charvat

Last Updated By:

Karel Charvat

Date Created:

03/07/2014

Date Last Updated:

03/07/2014

Actors

Abstract:

1. Public bodies – National and Regional Authorities providing meteorological information. 2. Farmers – owners of sensors 3. Experts – Agricultural and environmental. 4. Enterprises, Companies and SMEs – particularly farmers, growers, and agri-supply companies. The Open Sensor Network scenario will collect and monitor data from in-field sensors in two agricultural sites in Latvia and South Moravia in the Czech Republic. The basic approach will be for webservices to send various sensors’ proprietary protocols to a common database, that is accessible with open

140 www.foodie-project.eu Page 81 of 156


D2.2 Social Validation Methodology protocols. The scenario will be then extended to use the SDI4Apps cloud based tools to process/aggregate the data directly from the sensors on the fly in real-time. In all cases the end users will be able to monitor the ongoing situation using their PCs, tablets or Smartphones. Description:

The pilot will design and implemented interoperable middleware managing access to senor data. The solution will include the following functions: • • • • • •

Preconditions: Postconditions: Name of Dataset:

the

Plugging of sensors, Cataloguing sensors Sensor discovery Sensors measurement visualisation Access to sensor measurement using Open Interoperable Interface (SOS, KML, GeoJSON, JSON, TopoJSoné LOD access to sensor measurment

Operational in-field sensor networks. Interoperable access to large scale sensor measurement and visualisation and analysis of sensor measurement. Input Topographic information External sensors databases (for example Pesse, Senslog, FOODIE database

Name of the Output Dataset:

OpenSensorNet

Name of the Application

Smart Sensor Network


• • •

Frequency of Use:

Minutes, seconds

Existing Tool:

Senslog system

Development Type:

Recycle: SDI4Apps has to adapt this webservice from the SmartOpenData project 1. Plug in available sensor 2. Cataloguing available sensor 3. Discovery available sensors and select needed 4. Visualise measurement 5. Access measurement Open Access to measurement converging different sensors in Europe

Normal Course of Events:

Exceptions: Includes:

Visualisation client based on HSlayers Interoperable access to measurement (SOS, KML, JSON..( Semantic indexing

Sensor crowdsourcing Open Access

Special Requirements: User Validation:

Interoperable interfaces

• • Criteria of Success of •

User Engagement for plugin sensors Direct user interaction with open data access processes Usage level & Social Validation of Services that use Page 82 of 156


D2.2 Social Validation Methodology the Scenario

SDI4Apps Integrate VGI with low cost sensors in local web sensor networks • Increased access to harmonised & interoperable GI, L/OD& VGI data • SMEs, Students & Researchers developing new Apps Interoperation with P6 - Ecosystem Services Evaluation Pilot (possibly – to be other SDI4Apps Pilots determined when early prototypes are running). •

SDI4Apps Cloud Service • Model required •

Platform as a Service - PaaS Infrastructure as a Service – IaaS


Interoperable scalable access to sensors Scalable GI to LOD transformation and harmonisation service, from many heterogeneous database sources, including Senslog Scalable RDF Triple Storage service for LD (such as Virtuoso 141) Advanced Visualisation framework and API (of GI and nonGI components) Scalable intelligent deep-Web GI/LD Search and discovery with an open API Scalable Smart Sensor Networks and SensorML support, to extend the PPP FI ENVIROFY Specific Enablers 142

• • • • Assumptions:

To be discussed with different sensors producers and service providers

Notes and Issues:

BOSC will cooperate with CCSS and HSRS, It is expected that there will be cooperation with other projects such as FOODI and AgroIT

Dataset Dataset ID:

UC.15.01;DS.01

Dataset Name:

OpenSensorNet

Created By:

Karel Charvat

Last Updated By:

Karel Charvat

Date Created:

03/07/2014

Date Last Updated:

03/07/2014


Database will be based on Postgress and PostGIS. Sharing sensors measurement and will be based on the Senslog system

Dataset type:

Relational with potential access in RDF form

Availability:

• •

Does the dataset already exists? No Is the dataset already available, visible and public? No

141 http://en.wikipedia.org/wiki/Virtuoso_Universal_Server 142 See the ENVIROFI central repository of Specific Enablers (SE) for the environmental Usage Area within the Future Internet Public Private Partnership programme (FI-PPP) at http://catalogue.envirofi.eu/. This catalogue also presents the ENVIROFI pilot scenarios - concrete examples of adopting a combination of ENVIROFI Specific Enablers and FI-Ware Generic Enablers (GE) for the agri/environmental domain specific tasks Page 83 of 156


D2.2 Social Validation Methodology Format& Storage:

Relational, LOD

Size:

To be determined

Openness:

5

LOD Status:

TBC

LOD Functionality TBC Description: Access Rights:

Public domain


UC.15.01;AI.01

Application Name:

Smart Sensor Network

Created By:

Karel Charvat

Last Updated By:

Karel Charvat

Date Created:

03/07/2014

Date Last Updated:

03/07/2014


Sensors plugin, cataloguing, discovery Responsive HTML5 Browser/App on PCs, Tablets and Smartphones to access the Webservice (SOS, KML, JSON)

Availability:

Senslog prototype exist, has o be updated

Format:

• •

Graphical user interface – Standard HTML5 browser. Machine readable interface – simple and light RESTful webservice using JSON to allow App access. Supported functionality OGS SWE services / capabilities: KML GSON Interactive visualisation and filtering Plug In, cataloguing, discovery

5.5 Open Land Use Map through VGI Pilot Land use involves the management and modification of the natural environment or wilderness into the built environment such as fields, pastures, and settlements. It also has been defined as "the arrangements, activities and inputs people undertake in a certain land cover type to produce, change or maintain it" (DoW). Land use practices vary considerably across the world. The United Nations' Food and Agriculture Organization Water Development Division explains that "Land use concerns the products and/or benefits obtained from use of the land as well as the land management actions (activities) carried out by humans to produce those products and benefits." 143 As of the early 1990s, about 13% of the Earth was considered arable land, with 26% in pasture, 32% forests and woodland, and 1.5% urban areas. 143

FAO Land and Water Division Page 84 of 156


D2.2 Social Validation Methodology Land use and land management practices have a major impact on natural resources including water, soil, nutrients, plants and animals. Land use information can be used to develop solutions for natural resource management issues such as salinity and water quality. For instance, water bodies in a region that has been deforested or having erosion will have a different water quality than those in areas that are forested. Forest gardening, a plant-based food production system, is believed to be the oldest form of land use in the world Although the terms land cover and land use are often used interchangeably, their actual meanings are quite distinct. Land cover refers to the surface cover on the ground, whether vegetation, urban infrastructure, water, bare soil or other. Identifying, delineating and mapping land cover is important for global monitoring studies, resource management, and planning activities. Identification of land cover establishes the baseline from which monitoring activities (change detection) can be performed, and provides the ground cover information for baseline thematic maps. Land use applications of remote sensing include: • natural resource management • wildlife habitat protection • baseline mapping for GIS input • urban expansion / encroachment • routing and logistics planning for seismic / exploration / resource extraction activities • damage delineation (tornadoes, flooding, volcanic, seismic, fire) • legal boundaries for tax and property evaluation • target detection - identification of landing strips, roads, clearings, bridges, land/water interface

5.5.1

Open Land Use Pilot Scenario

On one hand, there are global mapping initiatives for mapping land cover (Corine CLC, Africa Cover, Global cover) and voluntary initiatives such as Geo-WIKI for updating global Land Cover Maps. The Geo-Wiki Project is a global network of volunteers who wish to help improve the quality of global land cover maps. Since large differences occur between existing global land cover maps, current ecosystem and land-use science lacks crucial accurate data (e.g. to determine the potential of additional agricultural land available to grow crops in Africa). Volunteers are asked to review hotspot maps of global land cover disagreement and determine, based on what they actually see on Google Earth and their local knowledge, if the land cover maps are correct or incorrect. Their input is recorded in a database, along with uploaded photos, to be used in the future for the creation of a new and improved global land cover map. On the other hand, there is no global nor European initiative for mapping land use. Land use is often mapped on local or regional levels. The INSPIRE land use represents scattered resources of varying quality and limited coverage in Europe. The Corine Land Cover (CLC) is a land cover map, not land use map. Moreover, the map is too generalised for regional and local purposes. The Urban Atlas is only for major European cities and does not cover rural areas and remote suburbs of cities. The need for a European land use map were expressed during the collection of requirements within the Plan4business project. The voluntary approach is the only way to perform the collection of data with minimal costs. This scenario will support Voluntary Open Land Use Mapping, and will include: • meeting the needs and requirements for European land use mapping; • producing an initial data set by combining existing data resources (OSM, CLC, Urban Atlas, National, Regional and Local Data); • publishing harmonised data sets; Page 85 of 156



adopting QAPP and provide quality control; evaluation of the effectiveness of the SDI4Apps platform, and limits and benefits of the solution in comparison with existing technologies; deploying a PC and mobile interface for data update.

The scenario will use a VGI approach to build on the Land Use work of the Plan4Business service platform for aggregation, processing and analysis of urban and regional planning data 144 and will be divided into the following steps: • •

• • •

Define a data model for land use mapping based on the INSPIRE HILUCS classification scheme Transfer existing data and build an initial Land use map from a combination of different sources: o Land use from OpenStreetMap o Part of the information from Land cover o National information sources such as RUIAN in the Czech Republic Make the Open Land Use Map publicly available Deploy the SDI4Apps mobile and desktop interface for updating the Open Land Use Map Deploy harmonisation tools for updating the Open Land Use Map using existing available open data

The Open Land Use Map will be freely available for download, and will be accessible through OGC interfaces, as well through the SDI4Apps API. The Open Land Use Map through VGI will use the following available global data sources: 1. European and global land use and land cover data including CLC, Urban Atlas, Global Cover, Africa Cover; 2. Land Use Data from Plan4business and Plan4all – it will include current and future land use data, the Open Land Use Map will build common database with Plan4business and will extend this database to other countries; 3. Regional, local, spatial and urban plans of partners – the regions will include their available plans and other related data to land use; 4. Publicly available land use data like data coming from the ELF and from other resources. The Apps will use and combine several distributed data layers, that could be used together (for example, the end user could see integrated data layers of polluted sites and tourism routes closely to these sites). As the open Land use mapping end users will include Professional spatial planners at local and regional level, the Apps will be both mobile and PC based. End –user engagement and their usage of the Apps will be monitored in task T2.3 and reported the Internal Validation Reports (D2.3.1/2/3). These will clarify, what is the way, that for example spatial planner in a municipality can use the application and what is the main benefit of it in this case. Use Case ID:

UC.15.02

Use Case Name:

Voluntary Open Land Use Mapping (VOLUM)

Created By:

Karel Charvat

Last Updated By:

Karel Charvat

Date Created:

2/07/2014

Date Last Updated:

2/07/2014

144 www.plan4business.eu Page 86 of 156


D2.2 Social Validation Methodology Actors

Abstract:

Description:

1. Public bodies – National and Regional Authorities responsible for spatial planed and land use. 2. Experts – Planning and Land Use experts and decision makers. 3. Enterprises, Companies and SMEs – related to Land Use. 4. Citizens – visitors and people interested in planning and land use in their local environment. 5. Students – interesting about thematic data 6. Farmers and forest owners – putting their information into the system 7. NGOs – interested in better information about land use mainly in sensitive areas 8. Researchers interested in Land use data analysis 9. Real estate business and investors interesting about land use analysis 10. System administrators – people responsible for managing data sets for certain regions VOLUM will build on the Land Use work of the Plan4Business service platform for aggregation, processing and analysis of urban and regional planning data to produce an Open Land Use Map. There were suggested data models for VOLUM and there were integrated initial data sets for certain EU regions. VOLUM will include a set of tools for updating data using new data sets, on line digitising data, controlling data sets and collecting additional information using smart phones, providing administration and validation of the data. Part of the solution will also be Open Access to data using view and download services, eventually accessing data using other interfaces like KML or JSON VOLUM will be composed from set of steps and will be supported by a set of tools focused on the single functionality of VOLUM, to: •

• • •

•

Publish a large data set on a server, which has to be integrated as part of VOLUM. It could be for example Spatial Plans or other large data sets. The operation is provided by external users. The publishing will include notification of administrator about new available data Harmonising published data sets into Open Land Use HLUCS classification – operation could be provided by external users of administrator Validate external data and integrate this data as a part of Open Land Use – operation will be provided by an Administrator Providing voluntary web based digitalisation and updating of data – new data are stored in temporary layer. Administrator is notified about data update. Validation and updating Open Land Use data from temporal layer by the administrator

Page 87 of 156



Preconditions: Postconditions:

Name of the Input Dataset:

Reporting of errors and improving information in Open Land Use Maps using Smartphones. Volunteers are sending classification of selected objects and its photo for controlling. The administration is notified about new data. • Validation of Voluntary reporting and updating of Open Land Use data • Publishing of Open Land Use data as view services, downloaded services using WFS) or other formats like KML, GeoJSON, TopoJSON The pilot will include demonstration activities of possible utilisation of data, but also tools. So the idea is, that in the future could be developed both globally, but also as a local application. Along with the SmartTouristData pilot, this pilot will aim to develop something global. However this does not mean, that some concreate apps will be developed only for Vidzeme, Zemgale or Sicily. For instance, Vidzeme has open data about polluted sites, that other partner regions might not have, and then it makes sense to create and validate a specific application with just one region’sl data, aimed at more specific target audiences. And it also makes sense in terms of pilot validation, since the project will not be able to validate a pilot application’s usage for example in Greece etc. Initial Land Use map has to be generated for all World. Other Reference data has to be prepared Users of SDI4 Apps platform are able to update data on a voluntary base Users of SDI4Apps platform are able to visualise and access data of Open Land Use in their applications using standardised formats CORINE, Urban Atlas, Global Cover, Spatial Plans, Topographic maps, Ortophotos, satellite images, OSM

Name of the Output Dataset:

Open Land Use Map


Open Land Use Wiki


Visualisation client Catalogue Editing client Client for uploading data Mobile client for data collection Client for data valuation

Frequency of Use:

Daily

Existing Tool:

Laymen, Hale, Mapcomposer

Development Type:

Recycle with new functionality. SDi4Apps has extended tools from Plan4business The users will be able to add new information to Open Land Use

Normal Course of Events:

Page 88 of 156

Thematic

Atlas,

Micka,

Geoserver,


D2.2 Social Validation Methodology Administrators will be able to validate and update data The users will be able to access Open Land Use as open data using a standardised interfaces. The pilot will aim to put together data from as many regions as possible, and also combine this data with other data, such as VGI, pen data of global scale. While coverage will not be equal, it is part of VGI to inform about data quality. So this has to be a basis of data models. The pilot will offer access also to some local and regional data and provide easy access for others including developers. The Open Land Use will be used as part of the Plan4all Open Data Platform

Exceptions:

It will be used also for business cases such as territorial decision or investment planning Includes:

Crowdsourcing, validation Open Access


Validation of data by administrators. It will require building a network of administrators. The community for data collection has to be built.

User Validation:

•

Criteria of Success of the • Scenario • • • Interoperation with SDI4Apps Pilots

User Engagement Usage level & Social Validation of Services that use SDI4Apps Increased access to harmonised & interoperable GI, L/OD& VGI data VGI Open Land Use Mapping SMEs, Students & Researchers developing new Apps

other P1 - Easy Data Access Pilot P2 - SmartTouristData P5 - Open INSPIRE4Youth Pilot P6 - Ecosystem Services Evaluation

SDI4Apps Cloud Model required

Service • • •

SDI4Apps Enabler Functions • required • • • • • •

Applications – Software as a Service - SaaS Platform as a Service - PaaS Infrastructure as a Service - IaaS Scalable crowdsourced/VGI real-time data collection with an Open API. Scalable Geo ‐ focused Crawler for automatic collection of OGC services endpoints representing spatial content available via the deep web. Validation and integration tools Scalable INSPIRE GI schema to LOD transformation and harmonisation service, with persistent URIs. Scalable RDF Triple Storage service for LD Semantic indexing infrastructure to transform GI to LOD Advanced Visualisation framework and API (of GI and non-GI components)

Page 89 of 156


D2.2 Social Validation Methodology Scalable publishing of harmonised GI and LOD data sets. Scalable fast PostGIS and concurrent PostgreSQL support, providing clustered real-time updates on all master databases. Scalable GeoServer implementation.

•

• •

Assumptions:

Will be clarified in discussions with other pilot partners

Notes and Issues:

HSRS, CCSS & AVINET will cooperate with other partners

Dataset Dataset ID:

UC.15.02;DS.01

Dataset Name:

Open Land Use Map

Created By:

Karel Charvat

Last Updated By:

Karel Charvat

Date Created:

2/07/2014

Date Last Updated:

2/07/2014


Vector data stored in databases including geometry (polygons} and attributes. Attributes has to include minimally classification with link to vocabulary translated classes codes into different languages, origin of geometry, origin of classification. There could also be a potential link to the original data

Dataset type:

Vector data with potential LOD access

Availability: Format& Storage:

• Does the dataset already exists? Partly • Is the dataset already available, visible and public? Partly Vector data

Size:

Not known now but it will be hundreds of Gigabytes

Openness:

3–5

LOD Status:

Will be clarified, it is not the main focus, LOD will be used mainly for classification and linkage to original data

LOD Functionality WBC Description: Access Rights:

Probably public domain, but it has to be clarified


UC.15.02;AI.01

Application Name:

Open Land Use Data Uploader

Created By:

Karel Charvat

Last Updated By:

Karel Charvat

Date Created:

2/07/2014

Date Last Updated:

2/07/2014


Layman and Hale tools from Plan4business allowing publishing of data by external users Page 90 of 156


D2.2 Social Validation Methodology Availability:

Exists as part of the Plan4all infrastructure

Format:

N/A

Supported functionality Data upload, data harmonisation / capabilities: Application ID:

UC.15.02;AI.02

Application Name:

Open Land Use Data Validator and Integrator

Created By:

Karel Charvat

Last Updated By:

Karel Charvat

Date Created:

2/07/2014

Date Last Updated:

2/07/2014


Application will allow administrators to validate and integrate voluntary data into a master data set.

Availability:

Not exist

Format:

N/A

Supported functionality Data validation and Integration / capabilities: Application ID:

UC.15.02;AI.03

Application Name:

Open Land Use Data Editor

Created By:

Karel Charvat

Last Updated By:

Karel Charvat

Date Created:

2/07/2014

Date Last Updated:

2/07/2014


Application based on HSlayers supporting on line Web editing of data

Availability:

Application exists, but has to be modified for the purposes of SDI4Apps

Format:

N/A

Supported functionality Online data editing with storage in temporally data set / capabilities: Application ID:

UC.15.02;AI.04

Application Name:

Open Land Use Data WIKI

Created By:

Karel Charvat

Last Updated By:

Karel Charvat

Date Created:

2/07/2014

Date Last Updated:

2/07/2014


Smartphone mobile application allowing the collection of pictures, description and position, and send data to a server

Page 91 of 156


D2.2 Social Validation Methodology Availability: Format:

Application exists, but has to be modified for the purposes of SDI4Apps N/A

Supported functionality VGI validation of data classification in Open Land Use / capabilities: Application ID:

UC.15.02;AI.05

Application Name:

Open Land Use Data WIKU

Created By:

Karel Charvat

Last Updated By:

Karel Charvat

Date Created:

2/07/2014

Date Last Updated:

2/07/2014


Portal allowing interoperable access to Open Land Use through Interoperable services

Availability:

Does not exist yet

Format:

WMS, WFS, KML, GeoJSON, TopoJSON, LOD?

Supported functionality / Open Access to Open Land Used Data capabilities:

5.6 Open INSPIRE4Youth Pilot – Regional Atlas of the Environment This pilot will be focused on the creation of an electronic version of a Regional Atlas focused on environmental data visualization. The main components of the environment will be introduced - water, air, soil, forests, nature protection, waste management, forest management etc. Each component has its actual condition measured - for this region. Depending on data availability this measured condition can be compared with a national standard (Czech Republic) or European standard. All this will be made available in an entertaining manner - no school textbooks. The main user group for this Atlas are students - higher grades of elementary schools, high schools and universities. That doesn't mean it will not be appealing for common adult people. The Atlas will have 2 forms - map application designed for PCs and also mobile app, that will cooperate with its PC counterpart. A printed version of this Atlas will also be prepared, but it isn´t included in this project. The mobile app will be made available for phones with the Android operating system – and will be available in the Google Store. The app will use geolocation to visualize actual data related to the Environment in each user’s current area. A very important part of the Atlas will be games connected with environment. For the young generation representing smart phone users is one of the enablers of new GI based applications. Spatial information helps young people to learn about the relationships between the environment, history and culture of different regions, but it could also support learning about European territories not only from a natural environment, history Page 92 of 156


D2.2 Social Validation Methodology and cultural point of view but also from a socio-economical point of view, at global level thanks to Internet. Online gaming and sharing of spatial information goes beyond the linguistic barriers, which are one of the most important constraints for the communication between different regions. Usage of spatial information in basic and secondary education is still at very limited levels. Some recent projects, such as the Czech regional project GeoHra (GeoGame) and their application to education in Czech schools (mainly Gymnazium Nad Kavalirkou) and experience of Secondary schools Gymnazium Bozeny Nemcove from the Lifelong Learning Naturnet Redime project 145 demonstrate the usability and also advantageous use of spatial information in secondary education, but also the potential contribution of young people to collecting environmental information. GeoGames was created in 2007 by Reach the World 146, a global education and mentoring nonprofit organisation. GeoGames challenges players to Build Planet Earth and Map Countries and Cities using fun graphics and sound effects on an animated 3D globe. The game focuses on cognitive concepts, such as spatial relationships (where the continents are in relation to each other and to the oceans), nesting (how a city is a unit within a country, a country is a unit within a continent), and how countries, continents and oceans have vastly different sizes (scale).. Designed to help educators teach and assess students' geography mapping skills, GeoGames can be played as a group activity or individually. Each level of the game is graded easy, medium, or hard. Players can track and record their completion times using the automated game timer, as well as print customized maps that reflect their progress at each level 147. Open INSPIRE4Youth will support creativity, technical capabilities, skills, knowledge and also relations, through gaming and sharing the geospatial content on the environment. Using new methods of digital cartography enables progress beyond linguistic frontiers. There are a great number of GI applications and new communication technologies relevant to the young world: for example active collection of environmental information, gaming and education. Open INSPIRE4Youth will be focused on more sophisticated methods where young people will be able to contribute to different environmental and social issues. The combination of both issues will be used as an educational methodology, when students will map their territories and also collect information about historical, environmental, cultural and socio economic issues.

5.6.1

Open INSPIRE4Youth Pilot Scenario

Innovation of our solution is based mainly in the following features: •

• •

We want as wide as possible application of Open Data which will be gradually prepared by transferring data from some selected agendas of Environment Department of Liberec Region Authority. Another source of data will be national information systems such as RUIAN. We also plan to have wide data use and map services according to specifications from the INSPIRE Directive (European, national and regional level). Base data will also be composed from data that are received by crowdsourcing. The Atlas will be focused on presenting entertaining and appealing ways of submitting facts. To achieve this we will use gamification elements such as virtual

145

www.naturnet.org www.reachtheworld.org 147 http://education.nationalgeographic.com/education/media/geogames/?ar_a=1 146

Page 93 of 156



• •

badges, achievements, ladders, chat, comments etc. This assumes advanced user profile maintenance. HTML5 games will be part of our Atlas. They will increase the attractiveness of statistical values and help to gain knowledge about the region (or nation or Europe) in and educational way. The main part will be in the user’s own language (Czech) but the user interface, most games and basic information will be in English. Open translation services will be linked to the Atlas.

The Atlas of Environment will integrate 1. National and regional environmental data related to the local and national environment. 2. Global environmental data such as data from the European Environmental Agency. 3. Data available through previous projects such as Plan4all, Plan4Business and others. 4. Crowdsourcing data This pilot scenario will cooperate with the Plan4business and ELF projects to generate a set of deployed applications for students and youth, that will include: • educational multilingual materials about regions; • game type materials with a focus on environmental and cultural heritage knowledge; • evaluation of the effectiveness of the SDI4Apps solution, and limits and benefits of the solution in comparison to existing technologies; • applications supporting mapping of local features by students (for this type of applications a QAPP will be applied). The pilot will mainly share common data with the Open Smart Tourist Data pilot. It will include: 1. Users' data (e.g. notes and comments of young people in particular; a. they will be collected with using web forms with an uniform structure based on a common data model; b. they will represent the most important data source from the point of view of individual presentation and acquisition of data. 2. Free and open-source global data (published mainly by State administrations or international organizations; e.g. VMAP /Vector Map/ or Urban Atlas). This group will also include statistical data related to the tourist industry (e.g. data from EUROSTAT, Wikipedia). 3. Partners' data (added by individual providers in the tourist industry, it includes new offers, news or improvements of services). 4. Free and open-source local and regional data (published mainly by local administrations, local non-profit organizations, living labs, local action groups etc.). 5. Crowd-sourced data and Volunteered Geographic Information (including products such as OpenStreetMap, Wikipedia). 6. Social media (comments, recommendations and opinions not only from common social media like Facebook, but also from social media focused on tourism). Use Case ID:

UC.03.02

Use Case Name:

Open INSPIRE4Youth

Created By:

Irena Koskova

Last Updated By:

Page 94 of 156

Irena Koskova © SDI4Apps Consortium 2014

D2.2 Social Validation Methodology Date Created:

08/07/2014

Actors:

Abstract:

Date Last Updated:

08/07/2014

1. Public bodies – European, National and Regional Education and Environmental Authorities. 2. Experts – Education and Environmental experts, Researchers & decision makers. 3. Enterprises, Companies, NGOs and SMEs – targeting and working with young people. 4. Citizens – young people. Electronic version of a Regional Atlas focused on environmental data visualization. The main components of the environment will be introduced. Each component has its actual condition measured - for this region. Depending on data availability this measured condition can be compared with national standards (Czech Republic) or European standards. All of this will be made in an entertaining manner - no school textbooks. The main user group for this Atlas are students - higher grades of elementary schools, high schools and universities. That doesn't mean it will not be appealing for common adult people. The Atlas will have 2 forms - map application designed for PCs and also mobile app. A very important part of the Atlas are games connected with environment. Open INSPIRE4Youth will extend and open Geogames on mobile platforms to support creativity, technical capabilities, skills, knowledge and also relations, through gaming and sharing of geospatial content on the environment. Using new methods and applications of GI and LOD, it will explore and progress beyond linguistic frontiers.

Description: Preconditions: Postconditions: Name of the Input Dataset: Name of the Output Dataset:

OpenINSPIRE4Youth


OpenINSPIRE4Youth Atlas of Environment


• •

Semantic indexing infrastructure, Visualisation framework.

Frequency of Use: Existing Tool: Development Type: Normal Course of Events:

Page 95 of 156


D2.2 Social Validation Methodology Exceptions: Includes: Special Requirements: User Validation:

• •

User Engagement Co-design of innovative “demand pull” services

Criteria of Success of the • Scenario • •

Usage level & Social Validation of Services that use SDI4Apps More Young People using GI services Local youth educational environmental & cultural heritage apps. • Increased access to harmonised & interoperable GI, L/OD& VGI data • Integrate data from users’, OD, crowd-sourced & social media. • SMEs, Students & Researchers developing new Apps Interoperation with other P1- Easy Data Access SDI4Apps Pilots P2 - Open Smart Tourist Data P4 – Open Land Use Map through VGI P6 - Ecosystem Services Evaluation SDI4Apps Cloud Service • Applications – Software as a Service - SaaS Model required • Infrastructure as a Service - IaaS SDI4Apps Enabler Functions • required • • • •

• •

Scalable crowdsourced/VGI real-time data collection with an Open API. Scalable RDF Triple Storage service for LD (such as Virtuoso 148) Semantic indexing infrastructure to transform GI to LOD Advanced Visualisation framework and API (of GI and non-GI components) Scalable intelligent deep-Web GI/LD Search and discovery with an open API Validation and integration tools Scalable publishing of harmonised data sets.

Assumptions: Notes and Issues:

Dataset Dataset ID:

UC.03.02;DS.01

Dataset Name:

OpenINSPIRE4Youth

Created By:

Irena Koskova

Last Updated By:

Irena Koskova

Date Created:

08/07/2014

Date Last Updated:

08/07/2014

148

http://en.wikipedia.org/wiki/Virtuoso_Universal_Server Page 96 of 156


D2.2 Social Validation Methodology Dataset description: Dataset type: Availability: Format& Storage: Size: Openness: LOD Status: LOD Functionality Description: Access Rights:


UC.03.02;AI.01

Application Name:

OpenINSPIRE4Youth GeoGame

Created By:

Irena Koskova

Last Updated By:

Irena Koskova

Date Created:

08/07/2014

Date Last Updated:

08/07/2014


Responsive HTML5 Browser/App Smartphones to access the service

Availability:

Does not yet exist.

Format:

• •

Supported functionality capabilities:

on

PCs,

Tablets

and

Graphical user interface – Standard HTML5 browser. Machine readable interface – simple and light RESTful webservice using JSON to allow App access.

/

5.7 Ecosystem Services Evaluation Pilot Ecosystem Services (ESS) are the direct and indirect contributions of ecosystems to human well-being. We can distinguish between provisioning, regulating, supporting and cultural services provided by ecosystems 149 . This pilot will be focused on the identification of spatial representation of the outcomes of ESS Evaluation with a focus on sustainable support of tourism. Whereas ecosystem services and their values are present in almost any landscape, one of the most important challenges is to assess the quality and quantity of the services provided in key natural areas such as protected areas, since these are often the source area of environmental services characterized by an exceptionally high productivity. Spatial representation in the most suitable digital form will be made

149

EEB for Local and Regional Policy makers, Chapter 1, page 16-17. Source: MA – Millennium Ecosystem Assessment (2005) ‘Ecosystems and Human Well-being: Synthesis’, Island Press, Washington DC. ( http://www.teebweb.org/resources/ecosystem-services/#tabbed_box_1) Page 97 of 156


D2.2 Social Validation Methodology available respecting the SDI requirements and recommendations and published via interfaces allowing presentation and further comparison of available content. The task of quantifying the value of ecosystem services is very complex. On one hand, the amount of scientific data needed, e.g. in the assessment of carbon sequestration or flood mitigation / erosion control of a given area would be enormous if it would be conducted in a comprehensive manner for larger areas. This is practically not realistic; therefore, scientific/primary data usually stems from relatively small plots, and is afterwards extrapolated based on assumptions and evaluating probabilities. On the other hand, another critical aspect is that there are different approaches possible for the mathematical assessment of some of the criteria. Consequently, depending on the approach, there are differences in the resulting value. In order to further compare the spatial interpretation of the ESS Evaluation outcomes from various areas at national and international level a pilot web application is foreseen to utilise the outcomes of the Open API adopted by the project. It is important to understand that biodiversity and ecosystem services have high intrinsic values that cannot be realistically measured and quantified. Whenever presenting economic values of protected areas, managers should emphasise that those values are only representing a small percentage of the benefits deriving from nature, natural resources and protected areas. While it is commonly acknowledged, that no calculation scheme results in an exact value on ecosystems there is an equally common understanding that a range of valuation techniques, if properly applied, provide sound approximations. Therefore, in monetary terms, approximations constitute valid references e.g. for protected area administrations or landscape planners from regional councils, in order to argue for pursuing or dismissing specific management options, particularly where investments and revenues have to be weighed against the continuity of ecosystem functions and services flow.

5.7.1

Ecosystem Services Pilot Scenario

The pilot will be focused on the identification of the spatial representation of the outcomes of Ecosystem Services (ESS) Evaluation with a focus on the sustainable support of tourism. The pilot will be built on previous results from the HLANDATA 150 and HABITATS projects and will closely cooperate with the SmartOpenData project, and will include: • SDI and linked data compliant datasets and services for ecosystem services evaluation; • identification of the spatial dimension and utilisation of the outcomes of ESS evaluation with a focus on sustainable support of tourism; • examination of national level data possible extension with more precise data collected on regional level; • exploitation of the results from the smeSpire project 151 related to training environmental data analysis professionals and the best practice catalogue of management of environmental data in Europe; • evaluation of the effectiveness of the SDI4Apps platform, and limits and benefits of the solution in comparison with existing technologies; • pilot web application build based on the open SDI4Apps API. The Ecosystem Services Evaluation will integrate 1. National and partners’ environmental data related to the local and national environment. 150 www.hlandata.eu 151 www.smespire.eu Page 98 of 156


D2.2 Social Validation Methodology 2. Global environmental data such as data from the European Environmental Agency. 3. Data available through previous projects such as EnviroGRIDS, Plan4all, Plan4Business and HABITATS. 4. Crowdsourcing data related to tourism and the environment. These data will be shared also with the other pilots. Use Case ID:

UC.09.01

Use Case Name:

Ecosystem services evaluation

Created By:

Zuzana Okániková, Last Updated By: Martin Tuchyňa, Peter Pastorek, Radoslav Považan

Martin Tuchyňa

Date Created:

04.07.2014

07.07.2014

Actor:

Abstract:

Description:

Date Last Updated:

1. Public sector representatives – National and regional authorities responsible for nature and biodiversity conservation and maintenance. 2. Researchers – Research and academia bodies involved in improvement of the ESS evaluation methodologies. 3. Citizens – contributors and consumers of the ESS related information. 4. Private sector stakeholders – investors and developers The use case is focused on integrating information resources for ecosystem evaluation with visualisation of the ecosystem services values for particular locations of the interest The use case will primarily address development of ecosystem services datasets based on linking diverse resources mainly from the biodiversity, biophysical and economy domains. These datasets will provide information on the value of the ecosystem at particular locations, in monetary or point form, which brings new dimensions to the impact of the evaluation on the state of the environment and the sustainable management of natural capital. The initial scope of the pilot will be at national level in Slovakia with the intention to extend the scope with information identified from lower levels of detail (regional, local, data or selected areas such as protected areas, areas of specific management, etc.) as well as from other countries. Public sector representatives as well as researchers will be able to search for information resources serving as an input into the ecosystem services identification and evaluation their value for a particular location. The first type of actors with their ability to address policy demand is driven mainly by the Aichi Targets (Strategic Goal D) and the EU Biodiversity Strategy to 2020 (Action 5) which promote consistent ecosystem assessments. Researchers will be able to improve existing methodologies in order to improve the current knowledge of ecosystem services Page 99 of 156


D2.2 Social Validation Methodology in maintaining human well-being and prosperity. Citizens, as well as potential investors, will be able to query the concrete value of a particular ecosystem service for the area of their interest. Preconditions:

Integration of heterogenic resources into a valuation map of ecosystems.

Postconditions: Name of Dataset:

the

Availability of the valuation map of ecosystem, including webapp allowing identification of ecosystem service type and value for particular location. Input 1. Corine land cover 2. Habitats and biotopes, protected areas 3. Statistical data 4. Economic data 5. Digital terrain model of Slovakia Note: The list of the datasets may be extended during the project implementation based on interaction with the stakeholders via social validation process. Some of the input datasets can remain with limited access licencing conditions.

Name of the Output Dataset of ecosystems services value Dataset: Name of the Application Addressed Semantic Facilities

Ecosystem services evaluator

SDI4Apps Searching, Visualisation Front-end

Addressed Pilot(s)

Ecosystem services evaluation

Priority:

High

Frequency of Use:

Daily

Existing Tool:

Hale, Geonetwork, Geoserver, Triplestore

Development Type:

Development based on the SDI4Apps basic cloud platform, extended functionality in combination with in house development

Normal Events:

Course

Alternative Courses:

of

1. Selection of the most suitable methodology approach to develop a valuation map of ecosystems 2. Discovery and identification of the relevant information resources for ecosystem evaluation 3. Processing of input resources into the valuation map of ecosystems 4. Publishing the valuation map of ecosystems through machine readable API 5. Visualisation of the valuation map of ecosystems and development of client webapp An important role will play selected methodology and availability of the relevant input resources. Based on that modifications can take place during the iterative development of the pilot.

Page 100 of 156


D2.2 Social Validation Methodology Exceptions:

So far, there is still discussion, whether there will be meaningful space to collect also crowdsourcing data for this use case, or extend the functionality with the user evaluation/validation of already available information.

Includes:

Open access, linking heterogenic resources


Validation of input data.

User Validation:

To be evaluated based on the methodology approach as well as social validation outcomes

Criteria of Success of • the Scenario • • • Interoperation with P1 other SDI4Apps Pilots P2 P3 P4 P5 SDI4Apps Cloud Service Model required

Availability of the Valuation map of ecosystems with UI and API Usage level & Social Validation of Services that use SDI4Apps Increased access to harmonised & interoperable GI, L/OD& VGI data Sustainable support of tourism with ESS methodology & datasets. - Easy Data Access Pilot – SmartTouristData – Open Sensor Network - Open Land Use Map Through VGI – Open INSPIRE4Youth • Applications - Software as a Service - SaaS • Platform as a Service - PaaS • Infrastructure as a Service - IaaS


Assumptions:

Analytical and modelling toolset Advanced Visualisation framework & API (of GI & non-GI components) • Scalable GI to LOD transformation and harmonisation service, from many heterogeneous database sources, including HALE 152 support. • Validation and integration tools • Scalable publishing of harmonised data sets. • Scalable Geo‐focused Crawler for automatic collection of OGC services endpoints representing spatial content available via the deep web. • Scalable INSPIRE GI schema to LOD transformation and harmonisation service, with persistent URIs. • Scalable RDF Triple Storage service for LD (such as Virtuoso 153) • Scalable fast PostGIS and concurrent PostgreSQL support, providing clustered real-time updates on all master databases. • Scalable GeoServer implementation Use case will provide the opportunity to better and easier communicate the role and benefits of ecosystem services to a

152 HUMBOLDT Alignment Editor, see https://joinup.ec.europa.eu/software/hale/description 153 http://en.wikipedia.org/wiki/Virtuoso_Universal_Server Page 101 of 156


D2.2 Social Validation Methodology wide range of communities (actors). Notes and Issues:

Complexity of the current ecosystem services evaluation knowledge status can cause above mentioned assumptions to be too ambitious.

Dataset Dataset ID:

UC.09.01;DS.01

Dataset Name:

Corine land cover

Created By:

Zuzana Okániková, Martin Last Updated By: Tuchyňa, Peter Pastorek, Radoslav Považan

Martin Tuchyňa

Date Created:

04.07.2014

07.07.2014

Date Last Updated:


Corine means 'Coordination of Information on the Environment' and it was a prototype project working on many different environmental issues. The Corine databases and several of its programmes have been taken over by the EEA. One of these is an inventory of land cover in 44 classes, and presented as a cartographic product.

Dataset type:

Input

Availability:

http://geo.enviroportal.sk/corine/

Format& Storage:

ESRI Shapefile, WFS

Size:

Cca 70 MB

Openness:

With licence

LOD Status:

2-3*

LOD Functionality Machine readable format Description: Access Rights: Dataset ID:

Open licence UC.09.01;DS.02

Dataset Name:

Habitats and biotopes, protected sites

Created By:


Martin Tuchyňa

Date Created:

04.07.2014

07.07.2014

Date Last Updated:


Selected INSPIRE habitats and biotopes of the Slovak Republic.

Dataset type:

Input

Page 102 of 156


D2.2 Social Validation Methodology Availability:

Dataset exists and it is publicly available

Format& Storage:

GML

Size:

Cca 20 MB

Openness:

3*

LOD Status:

Self contained dataset

LOD Functionality • Transformation (GML -> RDF, relational data -> RDF) Description: • Storage • Search • Federated querying • Visualization Access Rights: Open Dataset ID:

UC.09.01;DS.03

Dataset Name:

Statistical data

Created By:


Martin Tuchyňa

Date Created:

04.07.2014

07.07.2014

Date Last Updated:


Selected statistical data from national and EU statistical offices (e.g. EUROSTAT)

Dataset type:

Input

Availability:

To be investigated

Format& Storage:

To be investigated

Size:

To be investigated

Openness:

To be investigated

LOD Status:

To be investigated

LOD Functionality To be investigated Description: Access Rights: Dataset ID: Dataset Name:

To be investigated UC.09.01;DS.04 Economic data

Created By:


Martin Tuchyňa

Date Created:

04.07.2014

07.07.2014

Date Last Updated:

Page 103 of 156


D2.2 Social Validation Methodology Dataset description:

Relevant economic data from the national and international resources (eg. http://datanest.fair-play.sk/datasets)

Dataset type:

Input

Availability:

To be investigated

Format& Storage:

To be investigated

Size:

To be investigated

Openness:

To be investigated

LOD Status:

To be investigated

LOD Functionality To be investigated Description: Access Rights: Dataset ID:

To be investigated UC.09.01;DS.05

Dataset Name:

Digital terrain model of the Slovak republic

Created By:

Peter Pastorek

Last Updated By:

Martin Tuchyňa

Date Created:

04.07.2014

Date Last Updated:

07.07.2014


Relevant economic data from the national and internation resources (eg. http://datanest.fair-play.sk/datasets)

Dataset type:

Input

Availability:

ESRI GRID/To be investigated

Format& Storage:

To be investigated

Size:

Licensed

Openness:

To be investigated

LOD Status:

To be investigated

LOD Functionality Limited Description: Access Rights: Dataset ID:

ESRI GRID/To be investigated UC.09.01;DS.06

Dataset Name:

Dataset of ecosystems services value

Created By:

Martin Tuchyňa

Last Updated By:

Martin Tuchyňa

Date Created:

04.07.2014

Date Last Updated:

07.07.2014


Dataset containing information about the ecosystem service type and value for particular location

Page 104 of 156


D2.2 Social Validation Methodology Dataset type:

Output

Availability:

Dataset is not currently existing

Format& Storage:

ESRI GRID, WMS (WCS), RDF

Size:

N/A

Openness:

Open

LOD Status:

5*

LOD Functionality • Transformation (GML -> RDF, relational data -> RDF) Description: • Storage • Search • Visualization Access Rights: Open licence


UC.09.01.AI.01

Application Name:

Ecosystem services evaluator

Created By:

Zuzana Okániková, Martin Last Tuchyňa, Peter Pastorek, By: Radoslav Považan

Date Created:

04.07.2014

Updated Martin Tuchyňa

Date Last Updated:

07.07.2014


Web application allowing identification of ecosystem service type and its value for a particular location

Availability:

Not currently existing

Format:

• •

Supported functionality / capabilities:

Graphical user interface – Standard HTML5 browser Machine readable interface – RESTful, WFS, Sparql • Simple queries from graphical user interface • Full queries via machine readable interface

Related resources: http://www.pdx.edu/ecosystem-services/methods-and-data http://www.naturalcapitalproject.org/ http://www.biodiversity.ox.ac.uk/researchthemes/biodiversitytechnologies/ecosystem-services-evaluation-tool-ecoset/ http://fzp.ujep.cz/Projekty/VAV-610-5-01/HodnoceniBiotopuCR.pdf http://fzp.ujep.cz/projekty/HodnoceniFunkciASluzebEkosystemuCR.pdf http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home/

Page 105 of 156



5.8 Pilots’ requirements of the SDI4Apps Platform From the description of the pilots, the SDI4Apps Cloud Service Model requirements are summarised as follows: Pilots P1- Easy Data Access P2 - Open Smart Tourist Data P3 - Open Sensor Network P4 - Open Land Use Map Through VGI P5 - Open INSPIRE4Youth P6 - Ecosystem Services Evaluation

SaaS PaaS IaaS X X X X X X X X X X X X X X X X

Table 5 SDI4Apps Cloud Service requirements This is based on the standard Cloud Service Model 154

Figure 18 Cloud Service Models In addition, the initial set of required SDI4Apps Enabler functions that the pilots will require are grouped by the planned Basic and Extended Functionalities defined in the DoW (discussed in section 1.4), as follows:

154

As defined at http://en.wikipedia.org/wiki/Cloud_computing Page 106 of 156


Advanced visualisations Data harmonisation

1. Advanced Visualisation framework & API (of GI & non-GI components) 2. Scalable GI to LOD transformation and harmonisation service, from many heterogeneous database sources, 155 including HALE support. 3. Validation and integration tools 4. Scalable publishing of harmonised data sets. 5. Scalable crowdsourced/VGI real-time data collection with Open API.

Integration of mobile apps Interoperability 6. Scalable Geo ‐ focused Crawler for automatic collection of OGC services between local and endpoints representing spatial content global geospatial available via the deep web. models. 7. Scalable intelligent deep-Web GI/LD Search & discovery with Open API 8. Scalable Smart Sensor Networks and SensorML support, to extend the PPP FI 156 ENVIROFY Specific Enablers 9. Interoperable scalable access to sensors 10. Analytical and modelling toolset Linked Open Data 11. Scalable INSPIRE GI schema to LOD transformation and harmonisation service, with persistent URIs. 12. Scalable RDF Triple Storage service for LD 13. Semantic indexing infrastructure to transform GI to LOD 14. Scalable fast PostGIS and concurrent PostgreSQL support, providing clustered Scalable real-time updates on all master execution of databases. spatial models 15. Scalable GeoServer implementation

X

X

X

X

X

X

X

X

X

X

P6 - Ecosystem Services Evaluation

P5 - Open INSPIRE4Youth

P4 - Open Land Use Map Through VGI

P3 - Open Sensor Network

SDI4Apps Enablers

P2- Open Smart Tourist Data

SDI4Apps Functionality

P1- Easy Data Access


X

X X

X

X

X

X

X

X

X

X X

X

X X

X

X X X X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Table 6 SDI4Apps Functionality Enablers required by the Pilots While the planned SDI4Apps functionalities (Analytical and Modelling API, Data analysis and Multilingualism) are common for most of the SDI4Apps Enablers. These SDI4Apps 9 functionalities and 15 Enablers, and their inclusion into SDI4Apps, provide input to and are discussed in the D3.1 “Architecture Concept” deliverable. 155

HUMBOLDT Alignment Editor, see https://joinup.ec.europa.eu/software/hale/description See the ENVIROFI central repository of Specific Enablers (SE) for the environmental Usage Area within the Future Internet Public Private Partnership programme (FI-PPP) at http://catalogue.envirofi.eu/. This catalogue also presents the ENVIROFI pilot scenarios - concrete examples of adopting a combination of ENVIROFI Specific Enablers and FI-Ware Generic Enablers (GE) for the agri/environmental domain specific tasks. 156

Page 107 of 156

X



6. SUCCESS CRITERIA FOR THE SDI4APPS PLATFORM FOR EACH USER SCENARIO INSPIRE, GEOSS and Copernicus are politically driven top-down initiatives supported by experts from countries and organisations. It is important to see how INSPIRE and related initiatives reflect local, regional and national needs. Currently, there is a low awareness of these initiatives at regional and local levels, and the benefits for the local level are not clearly defined. Bregt 157 presented during the Joint Research Centre Cost Benefit Workshop in 2012 the relationship between costs and benefits for various governmental levels, depicted as follows:

Figure 19 Current costs & benefits of European SDI (A) and the targeted situation (B). SDI4Apps aims to be a solution that will strengthen the benefits at national and local levels, which is vital for successful implementation of INSPIRE, by demonstrating how SMEs, NGOs, regional developing agencies, municipalities and citizens can benefit from INSPIRE/Copernicus/GEOSS and how INSPIRE/Copernicus/GEOSS can profit from voluntary initiatives. There are different voluntary or bottom-up initiatives supporting SDI building. More and more localised information is collected by citizens. “Human observations” can become a part of the future real-time SDIs and serve as an input for spatial decision-making processes. Currently, data collection by citizens is higher than collection of data by public bodies, as depicted in the following:

157

Bregt, A., 2012. Spatial Data Infrastructures. Cost-Benefit Analysis in Perspective. JRC Workshop on Cost and Benefits of implementing the INSPIRE Directive. Page 108 of 156



Figure 20 New paradigm in data collection. 158 Local and community activities capture local knowledge in multimedia forms including videos, photos or oral histories. The collected information can contribute to up-to-date data. Volunteered geographic information (VGI) 159 is the harnessing of tools to create, assemble, and disseminate geographic data provided voluntarily by individuals 160 . Some examples of this phenomenon are WikiMapia, OpenStreetMap, and Google Map Maker. VGI can also be seen as an extension of critical and participatory approaches to geographic information systems 161 and as a specific concern within online or web credibility 162. These sites provide general base GI and allow users to create their own content by marking locations where various events occurred or certain features exist. In the context of voluntary data collection, an important part is the way that data is processed. An example is neogeography (New Age Geography) focused on combining geotagged data (e.g. KML 163 ) with a map interface for contextualised exploration. In neogeography data can be from volunteers (VGI) or from professionals, and can be open or with restricted access. Neogeography is closely related to Application Programming Interfaces (APIs), Web 2.0 and the mapping capabilities of the geospatial web. These methodologies bring serious challenges to SDIs and traditional forms of data acquisition, analysis, and publication 164. Neogeography cannot thrive without VGI. But to be of use, VGI must be utilised by neogeographic mash-ups. SDI4Apps aims to bridge between two divided worlds: 1. The top-down managed world of INSPIRE, GMES, GEOSS and similar initiatives represented by SDI experts,

158 Harris, T. & Lafone, F. 2012. Toward an informal Spatial Data Infrastructure: Voluntary Geographic Information, Neogeography, and the role of citizen sensors. In Čerba & Čerbová, eds. SDI, Communities, and Social Media. 159 http://en.wikipedia.org/wiki/Volunteered_geographic_information 160 Goodchild, M.F. (2007). "Citizens as sensors: the world of volunteered geography". GeoJournal 69 (4): 211–221. 161 Elwood, S. (2008). "Volunteered Geographic Information: Future Research Directions Motivated by Critical, Participatory, and Feminist GIS". GeoJournal 72 (3&4): 173–183. 162 Graham, M. (2010). "Neogeography and the Palimpsests of Place". Tijdschrift voor Economische en Sociale Geografie 101 (4): 422–436 163 Keyhole Markup Language, http://en.wikipedia.org/wiki/Keyhole_Markup_Language 164 Harris, T. & Lafone, F., forthcoming. Toward an informal Spatial Data Infrastructure: Voluntary Geographic Information, Neogeography, and the role of citizen sensors. In O. Čerba & K. Čerbová, eds. SDI, Communities, and Social Media. Page 109 of 156


D2.2 Social Validation Methodology 2. The bottom-up mobile world of smartphones, tablets, world of citizens and also world of thousands of micro SMEs developing applications.

Figure 21 Problem of two worlds. When as: • • • •

decomposing this issue, the SDI4Apps Social Validation will address questions such Can ordinary people profit from INSPIRE? Can INSPIRE profit from different voluntary initiatives? Is it possible on the basis of INSPIRE to build a successful business for thousands of European SMEs? Are we able to find a WIN–WIN strategy for public sector, private sector and citizens?

6.1 Convergence Computing

of

Cloud

and

Open

Source

SDI4Apps will demonstrate that Cloud Computing and Open Source development can converge by integrating open and scalable Cloud SDI using Open Source software. There are two approaches for the future ICT trends that can be considered as competitive. On one hand, there is Cloud Computing and on the other Open Source initiatives. It is necessary to mention, that ICT trends are mainly driven by big industries. The idea is to replace selling of software by selling infrastructures, platforms and services. Open Source Software is now supported by small and medium businesses but also by large industry. Open Source development is more focused on offering services as well as software integration. The vision is that the cloud will become a reality to overcome the problems of monopolies and will open possibilities for SME developers. For the future growth of the Open Source market, it is necessary to adopt such models which will attract software producers to publish their systems as Open Source. It is also important to find sustainable business models. The Open Source community goal is in principle not only to build communities, but also to open the chance to generate profit for primary producers of such systems and components. For Open Source developers and integrators the openness of software and possibility to modify existing tools is very important. This could be a problem for the Future Internet, if the code is not available as

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D2.2 Social Validation Methodology Open Source. Existing tools could then limit software and application developers. A compromise of both approaches seems to be optimal for the future. The current situation raises a number of essential questions for future developments in Cloud and Open Source services, to which the SDi4Apps Social Validation will contribute in a direct pragmatic way: • What will be the future development, data collection and data processing paradigms? • Will all SMEs move their computations into a cloud? – Or will new cloud computing developments constrain their market (licensing, distribution, market shares, customer retention, etc.)? – Or will we experience a combination of cloud and Open Source developments? If yes, in what way? • Does cloud computing permit Open Source models? – Is it true that it locks users into proprietary, non-open source software? • Will cloud computing be a “standard”? – Cloud computing is a model for enabling cost effective business outcomes through the use of shared application and computing services. The value, if possible, is better economics in the execution of business processes. Adopting a standard approach can help in reaching this level of efficiency. 165 • To what extent will cloud solutions guarantee reliability, security and persistence? • What will be the future of SDI? – Are local organisations able to deploy their own cloud-based infrastructures? – Under which conditions will such infrastructure be accepted by other local and regional players?

6.2 SDI4Apps Learning Community Space SDI4Apps will build a community around the SDI4Apps Cloud, which will be based on a core community represented by the project partners. This community will be extended by other related communities and through organising sprint code workshops and developers' contests. The SDI4Apps team is focused on building a community of companies and users to build a Living Lab/SSRI approach for social validation and wider uptake of project results. The main target groups of this community include: • The Open Source GIS community • Organisations dealing with the INSPIRE, GEOSS, Copernicus and UNSDI implementations. • GIS developers from other areas such as agriculture and tourism.

165 Cloud versus open source, http://thoughtsoncloud.com/index.php/2012/07/cloud-versus-opensource/ Page 111 of 156



Figure 22 Learning Community Space a) The core SDI4Apps community will be extended by other related communities (communities linked to SDI4Apps). These will be directly linked to the core community using their preferred platform or existing network. The third circle of communities includes interested groups that are thematically related and others that are just interested in the social validation.

6.3 Multilingualism An important problem being addressed by SDI4Apps is multilingualism. The problem of translation of geographical data and metadata has not yet been solved by INSPIRE. This represents a problem of global data utilisation by local communities. Translation of geographical data is a big challenge for all of the SDI community and its importance will grow in relation to different neogeography and VGI initiatives. SDI4Apps is addressing multilingualism by adopting LOD principles and connecting the spatial data with multilingual thesauri supporting translation of key words. For testing purposes translation from Italian, Czech, Slovak, Latvian and German into English will be provided in WP4 (Extended Functionality).

6.4 Criteria for the Evaluation of the SDI4Apps Tools for LOD pilot outputs Evaluation of the SDI4Apps tools is based on the scenarios of the last section, and must be carried out even before they are implemented. This is based on tabulated documentation of advance knowledge of the criteria and target evaluation scenarios, and as understood by developers. This will result in better implementation of the SDi4Apps platform’s tools. The self evaluation of the pilot scenarios using tables based on a classification of potential users who will use the results of this project, along with criteria for measurement of success of the SDI4Apps platform, using the following tables: 1) Social Validation of the Pilots by their own criteria. 2) Evaluation of tools for the creation of LOD 3) Evaluation pilot applications These will evaluate the quality of the SDI4Apps platform tools, including usefulness and usability. This perspective aims to answer the main question: “Does the tool that was developed meet the requirements defined in the specification of users?”

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D2.2 Social Validation Methodology Each evaluation criterion will not be evaluated by all evaluators but will be targeted at specific groups of evaluators. The potential user groups that will be addressed include: •

•

SDI4Apps Integrators: people who have to use heterogeneous GI to meet the requirements of their daily work (e.g. integration of LOD for complex analysis). They need the actual data and access this from different facilities potentially in different formats. They have to combine various data sources and harmonise them to make use of them for their own purposes. This group should understand the SDI4Apps platform as an efficient toolset to support the required data processing. They are mainly service providers. SDI4Apps Users: consist of a large group of people who want to solve a problem and decides to use LOD for their applications / purposes – they are not interested in the harmonization of data resources itself but only in its results. Two subgroups can be distinguished within this user role: o

SDI4Apps Development of LOD: users who are directly working with or create LOD. They transform heterogeneous GI sources and create either LOD in an already harmonised form, or LOD that doesn’t need harmonisation or integration at all. They make further application modules using LOD for end users.

o

SDI4Apps End-Users of applications: people who do not use LOD directly, they only use information arising from it (indirect use of LOD) or directly use applications. Most commonly they are users on a layman level, e.g. people using navigation systems, online routing services, etc.

All of the user groups are represented by members of the SDI4Apps consortium (pilots’ groups), but to ensure the wide use and sustainability of the results further users will be targeted to be involved in the project. In addition, other external experts will take part in the SDI4Apps social validation through the work of WP7 (Support for External Developers), and will include members of the SDI4Apps Review and Advisory Board. The following table shows the 6 pilots mapped according to the following criteria, which aim to encapsulate and summarise the key technical and usability requirements of the SDI4Apps platform tools: 1. Maintainability - Capability of the SDI4Apps platform to be modified a. Changeability - Capability of the software to be easy to change, adopt, enhance due to either new requirements or detected problems. b. Stability - Capability of the software to minimize unexpected effects from modifications of the software. c. Analysability - The capability of the software product to be diagnosed for deficiencies or causes of failures in the software, or for the parts to be modified to be identified. d. Testability - The capability of the software product to enable modified software validation. 2. Portability & Deployability - The capability of the SDI4Apps platform to be easily deployed and to be transferred from one environment to another a. Adaptability - The capability of the software to be modified for different specified environments without applying actions or means other than those provided for this purpose for the software considered. b. Installability - The capability of the software product to be installed in a specified environment. c. Maintainability - The capability of the framework to be modified. d. Coexistence - The capability of the software to co-exist with other independent software in a common environment sharing common resources.

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D2.2 Social Validation Methodology 3. Functionality - Capability of the tools to provide functions which meet stated and implied needs when the SDI4Apps framework is used under specified conditions a. Suitability - The capability of the software product to provide an appropriate set of functions for specified tasks and user objectives. b. Accuracy - The capability of the tools to provide the right or agreed results or effects. c. Interoperability - The capability of the tools to interact with one or more specified systems. d. Security - The capability of the software product to protect information and data so that unauthorized persons or systems cannot read or modify them; to authorized persons or systems are not denied access to them. e. Compliance - The capability of the tools to adhere to standards, conventions or regulations in laws and similar prescriptions. 4. Reliability - Capability of the tools to maintain the level of performance when used under specified conditions. a. Maturity - The capability of the tools to avoid failure as a result of faults in the software. b. Fault tolerance - The capability of the tools to maintain a specified level of performance in cases of software faults or of infringement of its specified interface. c. Recoverability - The capability of the tools to re-establish a specified level of performance and recover the data directly affected in the case of a failure. 5. Usability - Capability of the tools to be understood, learned, used and liked by the user. a. Understandability - The capability of the tools to enable the user to understand whether the software is suitable, and how it can be used for particular tasks and conditions of use. b. Learnability - The capability of the tools to enable the user to learn its application. c. Operability - The capability of the tools to enable the user to operate and control it. d. Attractiveness - The capability of the tools to be attractive to the user.

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Tools 1

Description

Metrics

Very easy (1), Easy (2) Average (3), Difficult (4), Very difficult (5)

Weight

Indicator

Questionary

Criterion

Lab testing

Main Criterion

project (Grant no.: 621129)

P1 - Easy Data Access; P2 - Open Smart Tourist Data; P3 - Open Sensor Network; P4 - Open Land Use Map - VGI; P5 - Open INSPIRE4Youth; P6 – EcoSys Svcs Evaluation.

Criterion ID


Applicable to

1.Maintainability - Capability of the framework to be modified a) Changeability - Capability of the software to be easy to change, adopt, enhance due to either new requirements or detected problems. b) Stability - Capability of the software to minimize unexpected effects from modifications of the software. c) Analysability - The capability of the software product to be diagnosed for deficiencies or causes of failures in the software, or for the parts to be modified to be identified. d) Testability - The capability of the software product to enable modified software validation. Maintainabilit Changeability Tools Group of testers evaluating if All components y installation it is easy to check after framework installation if all necessary components were properly installed and registered in the required tools Changeability Changes in Group of testers evaluating if standards it is easy the framework be adopted to changes in ISO, OGC standards. Changeability Enhancing the Group of pilot testers tools evaluating if it is easy to enhance the framework with new components. Stability General Group of pilot testers stability evaluating if the system fails frequently. Stability Stability Group of testers evaluating if although the system is stable although changes, changes of versions or addition Detection of of components, or if it is easy deficiencies or to diagnose deficiencies or failures. causes of failures through the messages retrieved. Analysability Logging Group of testers evaluating if capabilities all framework components has logging capabilities for all required system events.

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Tools 2

Analysability

Analysing components' capabilities Providing capabilities for tests

Installability

tools installability

Description

Metrics


Weight

Indicator

Questionary

Criterion

Lab testing

Main Criterion



Criterion ID


Applicable to

Group of testers evaluating if the API helps analysing the components' capabilities Testability Group of testers evaluating if the new version of components is provided to make tests before the release to end users. Testability Automatic Group of testers evaluating the informs framework ability to auto inform if problems are found. Portability 2.Portability and Deployability - The capability of the framework to easy deploy and to be transferred from one environment to another and a) Adaptability - The capability of the software to be modified for different specified environments without applying actions or means other than those provided for this purpose for the software considered. Deployability b) Installability - The capability of the software product to be installed in a specified environment. c) Maintainability - The capability of the framework to be modified. d) Coexistence - The capability of the software to co-exist with other independent software in a common environment sharing common resources.

Installability

Adaptability Adaptability

Group of pilot testers evaluates if the framework’s installation is described comprehensibly. Installation of Group of pilot testers API evaluating how easy/difficult is to install and run the framework components. Framework Group of testers evaluating implementation system’s communication with to other SW other software. Components in Group of testers evaluating the different adaptability of the tools in platforms different platforms.

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Tools 3

Weight

Description

Questionary

Indicator

Metrics


Applicable to

Functionality 3.Functionality - Capability of the tools to provide functions which meet stated & implied needs when the framework is used under specified conditions a) Suitability - The capability of the software product to provide an appropriate set of functions for specified tasks and user objectives. b) Accuracy - The capability of the tools to provide the right or agreed results or effects. c) Interoperability - The capability of the tools to interact with one or more specified systems. d) Security - The capability of the software product to protect information and data so that unauthorized persons or systems cannot read or modify them; to authorized persons or systems are not denied access to them. e) Compliance - The capability of the tools to adhere to standards, conventions or regulations in laws and similar prescriptions. Suitability Accuracy

Tools 4

Reliability

Usability Tools 5

Criterion

Lab testing

Main Criterion



Criterion ID


4.Reliability - The capability of the tools to maintain the level of performance when used under specified conditions. a) Maturity - The capability of the tools to avoid failure as a result of faults in the software. b) Fault tolerance - The capability of the tools to maintain a specified level of performance in cases of software faults or of infringement of its specified interface. c) Recoverability - Capability of tools to re-establish a specified level of performance and recover the data directly affected in the case of a failure. Maturity Fault tolerance Recoverabilty 5.Usability - Capability of the tools to be understood, learned, used and liked by the user. a) Understandability - The capability of the tools to enable the user to understand whether the software is suitable, and how it can be used for particular tasks and conditions of use. b) Learnability - The capability of the tools to enable the user to learn its application. c) Operability - The capability of the tools to enable the user to operate and control it. d) Attractiveness - The capability of the tools to be attractive to the user. Understandabilit y Learnability Operability Attractiveness

Table 7 SDI4Apps pilots mapped by the platform’s Tools’ Criteria

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The data gathered during the application of the evaluation methodology will be analysed using statistical methods. For each criterion an overall evaluation result will be calculated by summing up the values of the individual indicators that are part of this criterion and dividing the sum by the number of indicators There are some quantitative indicators which can be measured directly, e.g. response time, but the majority of indicators are qualitative indicators, meaning that they can only be measured indirectly (e.g. “learnability” of a new tool). For each indicator metrics will be defined that show how a given indicator can be judged and when a result is regarded as good or bad (e.g. threshold values). Example: Tools quality: Main criterion: Usability Criterion: Learnability Indicator: Ease of learning to perform a task using a tool Metrics: group of test users is observed while carrying out a typical task using the tool, time they need to learn how to carry out the task is measured, threshholds are set to determine which time spans are to be considered as very good (1), good (2), average (3), poor (4), very poor (5) The table will be filled in and these issues will be addressed in more detail and clarified in the Internal and External Validation Reports (D2.3.1/2/3 and D2.4.1/2)

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D2.2 Social Validation Methodology 621129)

project

(Grant

no.:

6.5 Success Criteria of the SDI4Apps platform for each User Scenario Based on the structured descriptions of the pilot scenarios in section 5, an initial mapping of each pilot’s own success criteria for the communities involved are summarised in the following table: Pilot & Validation approaches

Each Pilot Community’s Criteria of Success

P1 P2 P3 P4 P5 P6

Validation driven by the prospect of user engagement

Usage level & Social Validation of Services that use SDI4Apps Easy collection of information using smart phones & LOD More Young People using GI services Sustainable support of tourism with ESS methodology & datasets. Local youth educational environmental & cultural heritage apps.

X X

Integration of VGI into existing SDIs & LOD Integrate VGI with low cost sensors in local web sensor networks Increased access to harmonised & interoperable GI, L/OD& VGI data Integrate data from users’, OD, crowd-sourced & social media. VGI Open Land Use Mapping Availability of Valuation map of ecosystems with UI & API

X

Validation through direct user interaction with open data access processes

Reuse & share tourist information resources, channels & tools SMEs, Students & Researchers developing new Apps New tourism activities, visitors & jobs, and SME developed services.

X X

X X

X

X

Validation driven by codesign of innovative “demand pull” services

X

X

X

X X

X X

X X

X

X

X

X

X

X

X

X X X

X

X

X

Table 8 Validation approach & Initial mapping of each Pilot’s Success Criteria Success Criteria for the SDI4Apps platform in each of the 6 User Scenarios has a number of issues: 1. In some cases it may be difficult to evaluate each scenario. There may be licensing issues of software components specific to certain scenarios. 2. There may be limited access to certain data - either not permitted or restricted – and the source data may need to be modified 3. One option is to use training materials that will be prepared to assess the usability and functionality scenarios. 4. For the initial external evaluation scenarios it will be necessary to prepare a set of criteria / questions that can be targeted at specific problems and discuss scenarios for the next meeting of SDI4Apps. 5. Are the scenarios understandable for developers? The second evaluation exercise (usability and technical issues relating to the evaluation of the criteria) will be agreed and scheduled by the SDI4Apps consortium in 2015 (when all Page 119 of 156

X



project

(Grant

no.:

scenarios will have the necessary tools for demonstration and evaluation. This will be focused on ensuring that developers understand the user requirements. The results will be presented in the Initial, Interim and Final Internal Validation Reports (D2.3.1, D2.3.2 and D2.3.3) at the end of each year of the project. The final evaluation will be made on the basis of the updated selection of questions / criteria that will be formulated based on the results of the first two exercises and focused on specific categories of pilot scenarios stakeholders during 2015 and 2016. The analysis of the results of these reports and exercises will be given in the Interim and Final External Validation Report (D2.4.1 and D2.4.2) at the end of years two and three of the project. It will be important to keep the information gained from the evaluation of the SDI4Apps Scenarios, so that it can be used by the Scenario development team to check if the developed demonstrator meets the user requirements and if necessary add new requirements to the Scenario specification and to improve the pilot demonstrator. This will be especially important as it is intended that SDI4Apps Scenarios – where possible – will be sustained and further developed after the end of the SDI4Apps project. The following table shows the tools’ technical and usability criteria for the various pilots and their user communities, with the aim to summarise the key requirements of the SDI4Apps platform. This will be filled in as the pilot scenarios and their communities evolve, and will be reported in the Internal Validation Reports (D2.3.1, D2.3.2 and D2.3.3) as the project progresses. Main Criterion Maintainability

Functionality

Criterion

Indicator

Changeability

Scalability: addition of new data sources Changes in standards

Stability

General stability

Analysability

Detection of deficiencies or failures

Suitability

Suitability

Access to existing datasets, Loading to new datasets

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Description/ Questionnaire

Metrics

Applicable to

Users /pilot

The capability of the scenario software to be modified How easy is it to adapt the Scenario software to changes in ISO, OGC etc. standards? Testers evaluating if the system (=scenario 1. or 2.prototype) fails frequently How easy is it to diagnose deficiencies or causes of failures through the messages offered? Are reports of failures? The capability of the scenario software to provide functions which meet stated and implied needs when the scenario software is used under specified conditions Can a tester (or user) access existing data set of scenario prototype in new situation (or


D2.2 Social Validation Methodology 621129) Main Criterion

Criterion

Indicator

project


Metrics

(Grant

Applicable to

no.:

Users /pilot

deployment environment)?

Suitability

Capability of getting information on transformation definition

Interoperability

Interoperability of components

Compliance

Compliance of Services to ISO and OGC standards

Compliance

Compliance of metadata with Scenario metadata profile

Compliance

Compliance of Scenario prototype with Scenario specification

Covering Data harmonisation issues Covering Data harmonisation issues

Use of common data model in scenario Usage of framework components Usage of framework components

Usability

Understandability

Understandability of description Page 121 of 156

Can scenario prototype load new data set/object of a different region Provide information whether and how the original data set has been modified during harmonization. It is a report? Can the Scenarios prototype interact with the others components of the SDI4Apps framework? Is every service in the scenario prototype compliant to standards listed as mandatory in the handbook of standards Is a metadata from a new data source for the scenario application compliant to scenario new SDI4apps metadata profile? Has the Scenario prototype been developed in compliance with the Scenario specification? Has a common data model been created for the scenario? Which SDI4Apps common Framework components are used in the scenario prototype? Does scenario prototype provide a suitable test bed for the evaluation of different SDI4Apps Framework components The capability of the scenario to be understood, learned, used and liked by the user scenario specification and prototype documentation © SDI4Apps Consortium 2014

D2.2 Social Validation Methodology 621129) Main Criterion

Criterion

Indicator Multilinguality of description

Completeness of description

Learnability

Orientation in the system

Ease of learning to perform a task in use

project


Metrics

(Grant

Applicable to

no.:

Users /pilot

understandable? Is the Scenario specification and prototype documentation provided in multiple languages (spoken by the Scenario users)? Does scenario prototype documentation provide detailed, clear and understandable functional description of the scenario application? Can an end user operate the system and retrieve the results as specified in the scenario specification? How long does a user take to learn how to perform a specified task

Table 9 SDI4Apps Tools’ Requirements Criteria

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project

(Grant

no.:

7. SDI4APPS SOCIAL VALIDATION PLAN Social validation is compliance in a social activity to fit in and be part of the majority 166. It often leads not only to public compliance (conforming to the behaviour of others publicly without necessarily believing it is correct) but also private acceptance (conforming out of a genuine belief that others are correct). Social proof is more powerful when being accurate is more important and when others are perceived as especially knowledgeable. The monitoring methodology for the SDI4Apps contribution to social validation will be based on the following elements: • A methodological approach which is adaptive: focusing on monitoring and evaluating the innovative solutions of community groups within key processes of developments; • Promotion of a stakeholder’s active interaction and participation: the monitoring and evaluation methodology for assessing the effectiveness of ICT tools and in particular of the SDI4Apps platform. • Assessment of the impact of the adoption of new solutions, from the community’ s point of view, the feasibility and viability of the new solutions will be performed in a cycle of iterations where the interplay between diagnostics and assessment will be sought. The mechanisms for the assessment and process of social validation will include a series of indicators that provide the necessary insight on the impact and contribution of the project, as discussed in earlier sections. The SDI4Apps pilots’ validation aims to ground the development of data access, harmonisation and service architectures in concrete contexts of use as they are being developed. The pilot settings will involve real stakeholder partnerships involved in concrete and already-planned activities that all constitute use case examples of the added value of the harmonised data and related apps and services enabled by the SDI4Apps platform. It will cover both pilot platform integration and pilot execution. The pilot platform integration activity will carry out the integration work required by the individual pilot experiments and by the project as a whole. Where possible, existing partner platforms and data infrastructures will be used; in other cases, ad-hoc platforms will be integrated through mash-ups of existing available systems in order to meet the needs of the pilot user groups. External validation will start in the second cycle of the project’s community building. The intention of SDI4Apps is to attract external developers such as students, small companies etc. to the process of utilisation of the platform. This will be supported by developers’ workshops organised by the project, as well as two code sprints and a contest in WP7 (Support for External Developers). The goal is to extend the community around the platform for better feedback to developers. The social validation principles described here, will be used for assessment (in Tasks 2.3 and 2.4). Additionally, instruments often used by the Open Source community (such as tickets, blogs, user forums, bug tracking etc.) will be used. While implementing external validation, cooperation with WP8 (Dissemination and Business Planning) will take place. Particularly in organising interactive information campaigns to 166 HABITATS D2.4.1 Impact Assessment, May 2012, available at http://www.inspiredhabitats.eu/index.php?option=com_docman&task=doc_download&gid=12&Item id=82 Page 123 of 156



project

(Grant

no.:

attract potential platform evaluators and to spread information about the project, its outputs and use scenarios from local to national level.

7.1 SDI4Apps Social Validation Implementation Implementation of the SDI4Apps Social Validation methodology aims to be light and effective. It has been developed from the work and experience of projects such as HABITATS, Plan4All, Plan4Bussiness and SmartOpenData. The methodology basically consists of iteratively presenting the best practice SDI4Apps platform to the various stakeholder communities and asking them what they want of it and how well it meets their needs, and then improving it. The methodology involves the SDI4Apps partners, users’ and developers’ communities, meetings, observations, surveys and other evaluation techniques to track progress against agreed indicators, as discussed in the previous sections. The process consists of: 1. Identifying the stakeholder communities of: a. Users – represented by the 6 Pilots and operation of their user scenarios in WP6 (Internal Pilot Applications) i. Based on previous work and other projects. ii. As documented in the previous sections. b. Developers – i. represented initially by the consortium’s internal partners, and ii. later by the external developer communities that will be addressed through the activities of WP7 (Support for External Developers) 2. Asking the communities what they want in the context of what the SDI4Apps platform and tools can deliver, by: a. Providing the SDI4Apps infrastructure based on “best practice” architecture and tools from previous work b. Developing a coherent Social Validation Methodology, Plan and Indicators. 3. Checking if the communities are satisfied, by: a. Internal validation of the pilots and their users. b. External validation of user and developer communities using the SDI4Apps Platform to enable services beyond the pilots. The SDI4Apps Social Validation Methodology involves 1. Communities of stakeholders that the partners define who and where they are: a. End Users – particularly in the pilots b. Developers i. Internal – to provide the initial SDI4Apps Architecture and basic cloud functionality ii. External – to take-up the open source SDI4Apps APIs and modules for new services. c. Pilots – leveraged from previous and existing work to define Scenarios (as in section 5) in terms of i. Use Cases ii. Datasets iii. Applications and Services.

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project

(Grant

no.:

So Social Validation in SDI4Apps involves the 3 dimensions of Social, Technical and Validation activities to address all of the factors that need to be taken into account when carrying out a holistic social validation process, as illustrated in the following table over the 6 half-year periods (H) of the project: SDI4Apps Dimension Social Technical Validation

Activity

1H1

1H2

2H1

2H2

3H1

3H2

X X X

X

X

X

X

X

X X

X X

X X X

X X X

X X X

Social Validation Methodology Community Building & Support Basic Cloud Functionality Extended Functions & Data transformation Internal Validation & Pilots External Validation & OSS Communities

Table 10 SDI4Apps Social, Technical & Validation Activities In year 1 the project is undertaking the following twin track parallel work: 1. Technical: 2. Social:

Provide the SDI4Apps Architecture and Basic Functionality Build the Communities for Social Validation

Then in years 2 and 3 the project will focus on validation in the parallel tracks of: 1. Social: 2. Social: 3. Technical:

Undertake the Internal Community Validation and Pilots. Build external Communities & validation. Add extended functionality.

These SDI4Apps activities aim to achieve the following major aims of the project: SDI4Apps Dimension Technical

Year 1

Year 2

Social

Architecture & Basic Functionality Build Communities

Validation

Define methodologies.

Year 3

Extended Functions.

Wider SDI4Apps Services.

Internal Pilots, Internal Developers Apps & APIs

Wider Communities, External Developers New service possibilities.

Table 11 Major Aims of the SDI4Apps project The SDI4Apps Social Validation Plan by 3 monthly Quarters (Q) over the 36 months of the project is as follows: SDI4Apps Social Validation Plan Social Validation Methodology – light, effective

Q1

Q2

X

X

Identify & meet Internal Community Contacts. Setup Key Indicators Setup & Organise Pilots & Evaluation Process

Q3

Q4

X X X

X X X

Run the Internal Pilots & Evaluation Process Evaluate Pilot Apps & APIs.

Q5

Q6

Q7

Q8

Q9

Q10

Q11

Q12

X X

X X

X X

X X

X

X

X

X

X

X

X

X

Evaluate use of all SDI4Apps & Developers New Apps. External Validation Basic Cloud Functionality

X

Standard Functions

X X

Data Access & Harmonisation

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X X

X X

X X

X X

X X

X X

X X X

X X

X X



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Table 12 SDI4Apps Social Validation Plan execution & actions To monitor progress on this plan the SDI4Apps Social Validation Indicators (SVI) will be evolved based on the tables and discussion of section 6, as part of the Methodology. The SVIs indicate how well the SDI4Apps Platform is meeting the needs of its stakeholder communities. The SVIs’ focus is very much on WHAT, not HOW the various users’ needs are being addressed, particularly in the pilots. So while they map closely to the project’s metrics as defined in the DoW at a project level, the main focus on the SDI4Apps social validation process will be on each of the pilots, and what their scenarios and use cases aim to achieve. These will be defined by the user communities involved, particularly in the 6 pilot user scenarios in WP6. This work will be undertaken and coordinated in task T2.3 (Internal Validation), and its implementation and results will be documented in the Internal Validation Reports (D2.2.1/2/3). Building on Table 8 in section 6.5, a single validation template with criteria and indicators for all of the pilots will be aimed for, as in principle the pilots are similar in nature. However, as indicated In section 5, the pilots cover a broad spectrum and based on the user-empowerment inherent in the social validation methodology they may evolve suite differently. So this may not be possible. Therefore in the current plan the key indicators are proposed to be developed during the next half year in task T2.3, to be implemented on the ground by each of pilot lead partners, to ensure that the methodological approach will be the same across the pilots.

7.2 Evaluation Plan Set-up Setting up of the SDI4Apps Evaluation Plan, has begun with this definition of the Social Validation Methodology and initial identification and characterisation of the 6 pilot scenarios (in sections 5 and 6) focused on 1. Easy Data Access; 2. Open Smart Tourist Data; 3. Open Sensor Network; 4. Open Land Use Map through VGI; 5. Open INSPIRE4Youth/education 6. Ecosystem Services Evaluation. These pilots build on and leverage pilots from other projects to maximise their social validation of the SDI4Apps platform without getting bogged down in the detailed implementation of “green field” apps and services for the pilots. While the pilots will formally begin in WP6 in March 2015 (month 12), the social validation process begins in September 2014 (month 6), once the methodology is evolved, agreed and documented here. Initially the approach is very much top-down directed (as defined in this report) by the SDi4Apps partners. But once the process proceeds the voice of the users and other stakeholders will become much more proactive in driving the process and what they want, and we will be reported in the Internal and External Validation Reports (D2.3.1/2/3 and D2.4.1/2). But this will be an iterative process. As initially asking users what they want does not work, when they don’t see or understand what the SDI4Apps platform can provide, i.e. asking what people want from a service that does not yet exist ! In SDI4Apps – the basic functionality is being developed in parallel with the Social Validation development. The basic functionality of the platform will be architecturally-driven, based on best practice and best-of-breed components to provide the basic functionality in WP3 (Basic Cloud

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Functionality Deployment). This platform will be then presented to the User Communities in the Pilots to improve the system to their needs and requirements. At the initial the pilots, by 1. 2. 3. 4. 5. 6. 7.

setup stage, the partners will proceed with the social validation of each of meeting the various people involved and answering the following questions: Who is the contact person for each pilot scenario? When will it be known what app or service each scenario will involve? Where will the scenarios take place? What communities will be involved? What Users & User Cases will be involved? What will the success criteria be for each of the pilot scenarios? What indicators and metrics will be used to track those criteria for each scenario?

Annex C provides a suggested outline of those initial meetings, which are a critical milestone in the social validation process to clarify the stakeholders’ starting points as users and participants in the pilot scenarios. It is expected that this will evolve and changes as scenario’s use cases progress and the functionality of the SDI4Apps platform and tools evolve and enable more ambitious use cases. A key strength of the social validation user-centric approach is that it empowers users and the communities involved, and once they are so empowered they do tell the developers (the SDI4Apps partners here initially) what they want, and that can be quite different from what was originally envisaged. So the pilot scenarios as defined in sections 5 and 6, are likely to turn out quite different from what is described there! In this process, the partners will need to ensure that there is not an “explosion” of users’ participation and meetings, by involving just the coordinators of each projects scenario in the SDI4Apps Advisory Board.

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8. CONCLUSIONS & RECOMMENDATIONS SDI4Apps aims to bridge the gap between the top-down managed world of INSPIRE, Copernicus and GEOSS and the bottom-up mobile world of voluntary initiatives and thousands of micro SMEs and individuals developing applications based on GI, by adapting and integrating experience from previous projects and initiatives to build a cloud based framework with open API for data integration, easy access and provision for further reuse. SDI4Apps will be a solution that will strengthen the benefits at national and local levels, which is vital for successful implementation of INSPIRE, by demonstrating how SMEs, NGOs, regional developing agencies, municipalities and citizens can benefit from INSPIRE/Copernicus/GEOSS and how INSPIRE/Copernicus/GEOSS can profit from voluntary initiatives. The SDI4Apps platform and tools will be validated through 6 deployed pilot demonstrators that will be technically evaluated for: (a) the effectiveness of the approach for the Cloud, LOD and semantic services; (b) how well the proposed architecture can be adapted to different scenarios. (c) the limitations and benefits of the approach compared to existing technologies. This report defines criteria for measurement of success of the SDI4Apps platform methods for multi-stakeholder social validation and analysis for internal and external communities and also a set of indicators, which will be measured during the validation process based on a structured description of the pilot scenarios, as in section 5. The social validation will be provided by defining Use Cases in the User Scenarios of each pilot, according to the structured description defined in Annex B using the methodology described in sections 2 and 3. The evaluation will be provided on the basis of the following six pilots (as described in section 5): 1. 2. 3. 4. 5. 6.

Easy Data Access; Open Smart Tourist Data; Open Sensor Network; Open Land Use Map Through VGI; Open INSPIRE4Youth; Ecosystem Services Evaluation.

SDi4Apps adopts an approach that brings together the demand-driven power of the marketoriented solutions and the institutional legitimacy of INSPIRE/OD/LOD, which places the public interest before commercial needs. The approach is based on social validation, a process which engages “those who will adopt” within institutionally framed pilot experiments in the 6 diverse pilots. Thus central to validation of the SDI4Apps pilots are actions aiming to both build individual and collective assets by better understanding and potentially improving the effectiveness and transparency of the interaction amongst different organizational and institutional contexts which govern the use of these assets. In particular, SDI4Apps will extend to the cloud, the approach of the Reference Laboratory introduced by the HABITATS project 167. The Reference Laboratory is an environment with an open API based on Open Source components. This platform, which is an extension of the current INSPIRE architecture, incorporates basic principles of neogeography 168 and 167 www.habitats.cz 168 the use of geographical techniques and tools for personal and community activities or by a nonexpert group of users, see http://en.wikipedia.org/wiki/Neogeography Page 128 of 156



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Volunteered Geographic Information (VGI). These techniques will be used as the main building blocks of the SDI4Apps social validation. It allows users and data providers to test existing technologies, customise solutions for their purposes and thereby generate further research tasks through user-driven processes. The methodology for multi-stakeholder analysis adopted for implementation in the SDI4Apps social validation builds on the tradition of community-based participatory research169, asking a number of evaluative questions to assess how involved end-users and more generally the overall population are affected by a given intervention, project or programme. A key methodological reference point is constituted by the Living Labs/SSRI (Social Spaces for Research and Innovation) 170 approach adopted in SDI4Apps, aiming to deal with the social, organisational and institutional dimensions of innovation in parallel with the technical aspects, and to engage in validation activities with all user groups, stakeholders, and content providers in an open and inclusive way, supported by the SDI4Apps platform and tools. The SDI4Apps social validation process will report on the lessons learnt in each of the six pilots by adopting the following common structure for all of them: • Community Building and Engagement • Emerging Business Models • Added Value of the SDI4Apps platform • Interoperability with other SDI4Apps Pilots Community-based businesses foster trust, commitment, high-quality of products and services, accountability, social-environmental responsibility, business ethics, and “contagious commitment”. So in each of the 6 pilots of WP6, the project will nurture the Service Provider and User concept and make them both integral to the social validation participatory process so that it will become accepted as a necessary interchange and form part of an emerging business environment. It is envisaged that the robust stakeholder involvement central to SDI4Apps will not only generate sustainable economic returns through the interface between the business and the scientific community, but will guarantee a solid contribution to a knowledge-driven economy. Long-term sustainable implementation of the SDi4Apps platform will depend on three main pillars: 1. A large user community with strong commitment (based on involvement, trust and the benefits they receive from using the services) (WP2, WP7). 2. A reliable supply of global SDI data content, guaranteed large scale of services (WP5). 3. A thriving private sector of small enterprises (individuals, SMEs and NGOs) that provide value-added services of mutual benefit to all involved (WP7, WP8). From the structured description of the 6 pilots, the validation approach and initial mapping of each pilot’s metrics and criteria of success are identified in section 5. In addition, the SDI4Apps Cloud Service Model requirements are summarised and the initial set of required SDI4Apps Enabler functions that the pilots will require are listed. The SDI4Apps 9 functionalities planned in the Dow, and these 12 Enablers, and their inclusion into SDI4Apps, provide input to and are discussed in the D3.1 “Architecture Concept” deliverable. Implementation of the SDI4Apps Social Validation methodology will be light and effective. It has been developed from the work and experience of other projects such as HABITATS, 169 Vincent T. Francisco & Frances D. Butterfoss (2007), “Social Validation of Goals, Procedures, and Effects in Public Health”. Health Promotion Practice Vol. 8, No. 2, pp. 128-133 170 See http://www.c-rural.eu/index.php?option=com_content&task=view&id=74&Itemid=2 Page 129 of 156



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Plan4All, Plan4Bussiness and SmartOpenData. The methodology basically consists of iteratively presenting the best practice SDI4Apps platform to the various stakeholder communities and asking them what they want of it and how well it meets their needs, and then improving it. As concluded in section 2, SDI4Apps should contribute to a new strategic approach in the use of its cloud based Platform. The SDI4Apps’ pilots will most likely prove in real cases at the validation pilot sites that there is a large gap between what is required and what is needed. The bottle-necks will probably coincide with those already in previous work where sound knowledge based on timely, accurate, easily accessed geospatial and environmental information, remains one of the main obstacles in terms of sharing information across European institutions, national agencies, local jurisdictions and stakeholders. To finish, any SDI/LOD platform should be seen as an evolving concept that sustains (or mediates) various perspectives or stakeholders’ views. Depending on the user’s interest and role within the broader community, its design and implementation (as well as the corresponding assessment process) gets reshaped by a continuous negotiation and renegotiation with all involved actors. In addition, ‘space’ – or the ultimate object of any SDI/LOD Platform – is socially produced as well, which makes the validating role of sociotechnical platforms such as that of the SDI4Apps social validation even more important.

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ANNEX A: LINKED OPEN DATA This is a short introduction to Linked Data 171 What is the point of using Linked Data? The point of Linked Data is for webmasters to publish data in open, standardized formats that facilitate reuse by others. Others may include customers, suppliers and partners. If you’re a government authority, publishing Linked Data allows your data to be more readily used by other government agencies, the research community, and the general public. Organizations employing Linked Data are improving data quality, shortening development cycles, and significantly reduce maintenance costs. Enterprises are realizing a return on investment on Linked Data projects typically within 6-12 months. With traditional 3 tier data architectures, 60% of the full cost of an application is in application and data maintenance. Linked Data based solutions cost a small fraction of traditional applications due to efficiencies in data re-use, data exchange standards and cloud computing becoming more common. Unlike proprietary approaches, there is no vendor lock-in nor vendor dominance. Where can I see a demonstration of Linked Data? Round Stones operates an online Linked Data demonstration site at demo.3roundstones.net. This demonstration provides information regarding nuclear power plants located in the United States. It contains data gleaned from DBpedia, Open Street Maps, SEC Info, the U.S. Environmental Protection Agency’s Facilities Registry System, Substance Registry System and Toxic Release Inventory and Abt Associates report on corporate ownership. The purpose of this demonstration is to show the benefits of combining data from multiple sources and the ease and speed of creating Web applications using Callimachus. Why should we publish Linked Data when we already publish our data in a variety of formats on the Web? Providing data in open, standardized formats that facilitate reuse by other government agencies and/or departments, and third parties, e.g., journalists, academic, non-profit and corporate researchers and the general public. Generalized data sharing is made possible by the use of an international data exchange standard, the Resource Description Framework (RDF). Data in RDF allows for rapid combination of information from multiple data sources, including DBpedia (the RDF version of Wikipedia) and literally thousands of Linked Open Data sets available on the web. Publishing as RDF allows people to rapidly visualize ad hoc queries on maps, in tables, bar charts and many other common business views. Publishing Linked RDF is what Tim BernersLee, the inventor of the Web, calls “5 star” Linked Data. Linked Data publishing and use by

171 Taken from http://3roundstones.com/linked-data-101/. See also the official W3C Linked Data Glossary at www.w3.org/TR/ld-glossary/ An excellent introductory ebook is “Linked Data: Evolving the Web into a Global Data Space”, Tom Heath and Christian Bizer, 2011 available free at http://www.uni-koblenz-landau.de/campuskoblenz/fb4/west/teaching/ws1213/seminar-web-science/linked-data.pdf, while there an excellent course on Knowledge Engineering with Semantic Web Technologies, is available free at https://openhpi.de/courses/2d1ede48-4cc6-4a36-bcc4-6cb02e36b3ea Page 131 of 156



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enterprises has resulted in cost reductions in development time, deployment cycle, and maintenance compared with traditional data sharing mechanisms. How do I know that Linked Data is not a passing fad? Commercial companies recognize the market opportunity and are investing millions of dollars of R&D budget to create and support production tools improved creation, discovery and visualization of data on the Web. This includes Google, Oracle, IBM, Microsoft and Facebook. The UK Parliament pioneered publishing Linked Data with the backing and support of Sir Tim Berners-Lee, the inventor of the World Wide Web. Additionally, governments such as the US, Sweden, Germany, France, Spain, New Zealand and Australia are adopting Linked Data as a data publication and consumption model for Open Government Initiatives. The BBC is using Linked Data to operate large sections of its Web site and also used it to report on the last Olympics. While the term “Linked Data” is a relatively new term (circa 2007), it is based on International Standards and technologies that have formally and comprehensively presented, discussed and peer reviewed by literally hundreds of academic institutions, technology companies, and government agencies from around the world through the World Wide Web Consortium (W3C) for well in excess of a decade. How long do projects typically take to implement? A Linked Data Approach implies “cooperation without coordination.” This means that all members of an organization are not required to agree on schema, in advance or at any point in the development effort. Instead, a Linked Data approach recognizes that there is no one way to describe an organization, its products or services. Instead, a Linked Data approach embraces that individuals possess knowledge within their area of expertise and that they should be able to describe business process, rules and their data with both flexibility and standards. Are there any gotchas? a) There are several issues when adopting Linked Data that could become ‘gotchas’: Care must be taken to avoid biasing the value of high quality datasets by tightly coupling them to specific high profile applications. In short, do not do to your Linked Data what MDM did to your relational databases. Recognize that the core benefits of Linked Data involve the combination of data with data from other sources. Successful Linked Data projects produce generic, reusable data that may be combined with data from other sources to allow applications not yet conceived. Think reuse, not specific uses. b) Openly publishing data, be it Linked Data or not, must be undertaken under appropriate licensing which is unambiguous, appropriate, unrestrictive, and realistic as possible. We offer more detail below under “Risks”. c) Avoid “triplifying” data by automatic script. Triplifying data by script is not the same as creating well-structured Linked Data suitable for building applications. Proper data modelling is an essential first step. Efforts to automatically generate billions of RDF “triples” and publish them on the Web is not the same as producing high quality data sets of properly modelled data. d) People and organizations experienced with data modelling in RDF are still relatively rare. As one embarks on an effort to convert a dataset, what are the factors that determine conversion cost? a) What makes a dataset complex or simple

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Decisions on exposing a data set should based on usefulness to others. Usefulness is a measure of its ability to be used by others, both intra-agency, interagency and by the public. Only data of general usefulness should generally be published as Linked Data; agency- or application-specific data is not always useful to the rest of the world. The following are indicators of, but not hard and fast rules about, what factors impact the time required to expose data that is useful to others. More complex relational data models (say 60 or more tables) are more time consuming and complex to model, and therefore the time required is slightly longer, (measured in weeks however, not months or years); Data sets that require a prior knowledge of the agency organization, e.g., structure, regulations, workflow, internal vocabularies (e.g., for naming conventions) require meetings between data modellers and internal specialists; Domain specific data sets (e.g., geography, chemistry, physics or complex regulation) may require specialized domain expertise that may be harder to find or schedule. b) What does it cost to host RDF? There is no one size fits all answer on pricing, however the factors are all familiar to IT managers and procurement departments. The cost of modelling Linked Data and hosting it is based on several components including: • Time required to remodel data, typically measured in several weeks; • Frequency and size of updates; • Access, including query volume; • Applications (if applicable) based on Linked Data sets. Technology teams accustomed to managing hardware, networking, and service level agreements for traditional 3 tier applications will understand similar components to hosting a Linked Data service. Hosting is quickly becoming commoditized in terms of pricing. The value proposition should focus more on the service level agreement, patches and upgrades, security and other features that are vital to any production data or application service. Data consisting of millions of rows in a relational database is typically easy and inexpensive to host. There are economies of scale, hosting more data sets is not necessarily proportionally more expensive. The value proposition in using Linked Data not on the lower cost to host the data (RDF triples), however, the ability to provide high availability production managed services using Linked Data. There are software-as-a-service options which provide an easy scalable option in the early stages while enabling analysis of medium to long-term possibilities as the profile of the data and its use is established. c) What is the cost of putting up a new version of the data? This is dependent on the quantity of data, quality of modelling, frequency and size of updates, plus the ability of the chosen store to take live updates. The cost is often negligible and included in the cost of a hosting contract. Once the data is properly modelled, scripts are run to automatically convert data to Linked Data (as RDF triples) on a routine basis (e.g. hourly, daily, weekly) What about costs with a Linked Data approach?

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Traditional data warehouse projects require significant upfront coordination. The cost of vocabulary creation and/or schema alignment, creating data dictionaries and building applications involves teams of typically 6-12 analysts, data modellers, programmers and security specialists. By comparison, Linked Data applications are typically modelled within a 30 day sprint and applications can be created in hours. With emerging tools that are commercially supported, developers can host Linked Data applications on the cloud. Thus, within two months a reasonably complex data set can modelled, converted as Linked Data, and made available with powerful navigation and visualization features in less than two months on average. I’ve heard that in the future, graph data may make relational data bases obsolete. Is that true? Please explain. No, that is not true. They are different tools for different jobs. Both are very necessary to managing data in the modern information technology landscape. Relational databases are excellent at providing highly tuned access to structured, predefined data for typically pre-defined queries. There will be a significant need for this for a long time to come; they will not be obsolete in the foreseeable future. RDBMS are well suited for what they do well. Relational systems and applications built on relational databases, do not excel in handling data that is neither pre-defined in terms of model nor relationship. When you are exploring how data is inter-related, in order to learn about trends, patterns or things implicit in the data, is when you should consider a graph or Linked Data view of data. This is particularly relevant to intelligence applications, scientific research and many other types of applications where you don’t exactly know in advance what you are looking for. Relational databases are difficult and expensive to combine. Linked Data approaches are making rapid inroads in areas where data must be combined from multiple relational databases. Again, relational databases and Linked Data complement each other in such scenarios. We believe will continue to be a place for both relational- and graph-based data, both supporting each other both within the enterprise and externally via the World Wide Web, as Linked Data. As a manager, should I consider developing in-house expertise to assist program SMEs with producing Linked Data? If I do, how can my organization assess the quality of what is being produced? It is likely that your organization already has contractors and in-house staff familiar with the organization’s important data assets. Familiarity with Linked Data tools and techniques will come with time and should not be considered daunting. Once data is converted to RDF, there are Web based tools and interfaces to explore and view the data. One of the important features of Linked Data is that, developers can programmatically query the data through a SPARQL endpoint, allowing them to view the content. This is similar but more flexible to a “view” in SQL. SPARQL query capability can be locked down for use by only authenticated personnel, or can be made available more widely, depending upon the use case. There are techniques that are identical to the validation process performed on relational data by developers and data curators. These are different for Linked Data, however the concepts for data validation are similar to anyone who is a relational database professional. Your data experts will recognize the data in the RDF format. There are Linked Data tools, such as Callimachus, an Open Source

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Linked Data management system 172, to “follow your nose” and explore the data which is very powerful. Callimachus has a wiki-like interface, and a Class-based template engine that allows you to visualize and create Linked Data easily and quickly. With proper authentication, a user can update the underlying data in the graph database which is very useful. Access to a small agile team who can guide and work within the agency on Linked Data issues is advisable. Practically speaking, not every agency will be able to have an in-house expert on Linked Data. However, if the agency has an office of information access and/or management (such as EPA’s OEI), it is logical that this team’s responsibilities would include participation with other agencies, standards groups (W3C, others), and at conferences discussing best practices with agency and other teams supporting the agency’s mission. What should the next steps be? What (if any) training would our staff need? Although Linked Data is no more complex than traditional data modelling, it does require a different way of thinking focused on expressing relationships through URIs. Just as an agency works with an in-house or contractor data modelling expert, the same would be true with Linked Data. There is both data subject domain expertise required, as well as, specialization in data modelling strategy and tactics. Introductory training, best applied to small groups over a few days typically scheduled over 6-8 calendar weeks, is needed to discuss the differences between traditional vocabulary development and modelling approach for Linked Data. Experience has shown that these new generic techniques are then best supported and developed with situation specific workshops and/or mentoring as confidence grows. What hardware/software purchases are necessary? Many of the tools used for Linked Data are open source, including simple scripts and operating system commands, the use of which is openly shared within a community on the web. There is no cost associated with such tools. The storing and publishing of Linked Data can be handled by a simple web server. However, many more benefits flow from being able query that data, which requires it to be held in a linked data store, or RDF database. These are available as open source or proprietary services that you can host yourself or as a platform-as-a-service (PaaS) managed service. Correct configuration of Web servers to publish Linked Data (e.g. using correct ContentType information) is essential to reuse. Failure to understand Web standards can compromise an otherwise useful implementation. Therefore, care should be taken to have Linked Data reviewed by someone with relevant experience. What human capital / infrastructure needs are required to support this kind of work? This depends on the size of organization, the amount of data, and the rate of change to data. Experience has shown that having a small group/team of Linked Data aware people who can evangelize, help, support, guide and monitor a wider organization works well. What are the steps to creating a data-driven application? In practice, this approach requires speaking with one group at a time and exposing each RDBMS via either as real-time SPARQL query or periodic dump that is converted to an RDF format. Next, applications are rapidly created by Web developers using data-driven application tools and one or more Linked Data sets.

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Open data strategy will help tackle poverty and reduce corruption 173 Sir Tim Berners-Lee, founder of the World Wide Web, has called on governments around the world to open up their data to the public in the same way that the UK has. The Internet pioneer believes that releasing publicly held data to the public and software developers will help fight poverty, boost innovation, empower citizens and reduce corruption. Speaking at the Open Government Partnership Summit in London, on 4th November 2013, Berners-Lee revealed a report called the Open Data Barometer 2013 174, which shows that the UK has the most advanced open data policy. The report, a joint project between the World Wide Web Foundation and Open Data Institute, is an investigation into how many countries are allowing open data policies. “The Open Data Barometer is an important part of the puzzle and a good snapshot of where we are now,” claimed Berners-Lee. “What’s been brilliant in the UK is we got a project in the Cabinet Office to put a lot of data online quickly.” However, Berners-Lee said the UK is “only 20% of the way there” when it comes to open data, adding that the nation has some serious challenges ahead. “There’s a lot to do but there’s a massive agenda,” he said, pointing out that there’s no open data that allows you to turn a postcode or address into a latitude and a longitude. In the report, the US, Sweden, New Zealand, Denmark and Norway came immediately after the UK, out of the 77 countries surveyed. Berners-Lee said only one in 10 of the countries that promised to open up data has actually delivered. More than half (55%) of the countries included on the report have formal open data policies in place, but many of these governments will not release certain datasets, including company registers and land registers that could provide valuable information to the public and mapping data that could be used by developers behind apps like Citymapper 175. Criticisms of Open data Initiatives While the arguments concerning the benefits of open data are well established and include contentions that open data lead to increased transparency and accountability with respect to public bodies and services; increases the efficiency and productivity of agencies and enhances their governance; promotes public participation in decision making and social innovation; and fosters economic innovation and job and wealth creation. There are potential problems affecting, and negative consequences of, open data initiatives. Four criticisms 176 include: a. Open data lacks a sustainable financial model b. Promotes a politics of the benign and empowers the empowered c. Lacks utility and usability d. Facilitates the neoliberalisation and marketisation of public services. While these critiques do not suggest abandoning the move towards opening data, they do suggest that open data initiatives need to be much more mindful of what data are being 173 http://www.techcentral.ie/berners-lee-exhorts-governments-to-follow-open-datastrategy/#ixzz2jmknz1Bh 174 http://www.opendataresearch.org/project/2013/odb, full report at http://www.opendataresearch.org/dl/odb2013/Open-Data-Barometer-2013-Global-Report.pdf 175 http://citymapper.com/ 176Taken from http://www.nuim.ie/progcity/2013/11/four-critiques-of-open-data-initiatives Page 136 of 156



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made open, how data are made available, how they are being used, and how they are being funded. For SDI4Apps these issues will be explored in the WP6 Evaluation and Assessment with User Groups, and the WP7 Exploitation sustainability plans.

Global Open Data Initiative Declaration Declaration A Citizens’ Call to Action on Open Data 177 Preamble Governments exist “by and for the people”. The data they collect (or fund others to collect) in the course of carrying out their statutory duties also belongs to the people, and in the 21st century it is fast becoming one of the most valuable public goods we have – yet it often remains inaccessible or unaffordable to the vast majority. The Global Open Data Initiative aims to make Government data openly available to all – available for anyone, anywhere to download, use, re-use and redistribute without charge for any purpose. We welcome government and multi-stakeholder efforts to advance open government data, and we seek to contribute to their success. However, to ensure that such efforts deliver real and sustained benefits for citizens, it is essential that civil society comes to the table with its own strong vision, ideals and demands. The Global Open Data Initiative seeks to engage and unite as broad a civil society constituency in a shared vision of the role of open data in accountable, inclusive and participatory governance. In a well-functioning democratic society, citizens need to know what their government is doing. To do that, they must be able freely to access government data and information and to share that information with other citizens. Citizens’ core right to open government data arises from its increasingly critical role in enabling us to hold our governments accountable for fulfilling their obligations, and to play an informed and active role in decisions that affect us. In addition, opening up government data creates new opportunities for SMEs and entrepreneurs, drives improved efficiency within government, and advances scientific progress. The initial costs (including any lost revenue from licenses and access charges) will be repaid many times over by the growth of knowledge and innovative data-driven businesses and services that create jobs, deliver social value and boost GDP. We call on governments everywhere to take measurable, time-bound steps to: 1. Make data open by default:

Government data should be open by default, and this principle should ultimately be entrenched in law. Open means that data should be freely available for use, reuse and redistribution by anyone for any purpose and should be provided in a machinereadable form (specifically it should be open data as defined by the Open Definition and in line with the 10 Open Data Principles). Government information management (including procurement requirements and research funding, IT management, and the design of new laws, policies and procedures) should be reformed as necessary to ensure that such systems have built-in features ensuring that open data can be released without additional effort. Non-compliance, or poor data quality, should not be used as an excuse for non-publication of existing data. 177 From http://globalopendatainitiative.org/declaration/#sthash.81JKyqZr.dpuf Comments are invited on this declaration in the current commentable version of the above. See also their Declaration announcement blog post. Page 137 of 156



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Governments should adopt intellectual property and copyright policies that encourage unrestricted public reuse and analysis of government data. 2. Make the process people-centred (or “put the users first”):

Experience shows that open data flounders without a strong user community, and the best way to build such a community is by involving users from the very start in designing and developing open data systems. Within government: The different branches of government themselves (including the legislature and judiciary, as well as different agencies and line ministries within the executive) stand to gain important benefits from sharing and combining their data. Successful open data initiatives create buy-in and cultural change within government by establishing cross-departmental working groups or other structures that allow officials the space they need to create reliable, permanent, ambitious open data policies. Beyond government: Civil society groups and businesses should be considered equal stakeholders alongside internal government actors. Agencies leading on open data should involve and consult these stakeholders – including technologists, journalists, NGOs, legislators, other governments, academics and researchers, private industry, and independent members of the public – at every stage in the process. Stakeholders both inside and outside government should be fully involved in identifying priority datasets and designing related initiatives that can help to address key social or economic problems, foster entrepreneurship and create jobs. Government should support and facilitate the critical role of both private sector and public service intermediaries in making data useful. 3. Provide no-cost access:

One of the greatest barriers to access to ostensibly publicly-available information is the cost imposed on the public for access–even when the cost is minimal. Most government information is collected for governmental purposes, and the existence of user fees has little to no effect on whether the government gathers the data in the first place. Governments should remove fees for access, which skew the pool of who is willing (or able) to access information and preclude transformative uses of the data that in turn generates business growth and tax revenues. Governments should also minimise the indirect cost of using and re-using data by adopting commonly owned, non-proprietary (or “open”) formats that allow potential users to access the data without the need to pay for a proprietary software license. Such open formats and standards should be commonly adopted across departments and agencies to harmonise the way information is published, reducing the transaction costs of accessing, using and combining data. 4. Put accountability at the core:

Open Data needs to mean more than selective release of the datasets that are easiest or most comfortable for governments to open. It should empower citizens to hold government accountable for the performance of its core functions and obligations. At a minimum, governments should release datasets that are fundamental to citizen-state accountability and underlie key policy debates and decisions, including: (TBD list of data priorities goes here) Governments should create comprehensive indices of existing government data sets, whether published or not, as a foundation for new transparency policies, to empower public scrutiny of information management, and to enable policymakers to identify gaps in existing data creation and collection. 5. Invest in capacity:

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Governments should start with initiatives and requirements that are appropriate to their own current capacity to create and release credible data, and that complement the current capacity of key stakeholders to analyze and reuse it. At the same time, in order to unlock the full social, political and economic benefits of open data, all stakeholders should invest in rapidly broadening and deepening capacity. Governments and their development partners need to invest in making data simple to navigate and understand, available in all national languages, and accessible through appropriate channels such as mobile phone platforms where appropriate. Governments and their development partners should support training for officials, SMEs and CSOs to tackle lack of data and web skills, and should make complementary investments in improving the quality and timeliness of government statistics. 6. Improve the quality of official data:

Poor quality, coverage and timeliness of government information – including administrative and sectorial data, geospatial data, and survey data – is a major barrier to unlocking the full value of open data. Governments should develop plans to implement the Paris21 2011 Busan Action Plan, which calls for increased resources for statistical and information systems, tackling important gaps and weaknesses (including the lack of gender disaggregation in key datasets), and fully integrating statistics into decision-making. Governments should bring their statistical efforts into line with international data standards and schemas, to facilitate reuse and analysis across various jurisdictions. Private firms and NGOs that collect data which could be used alongside government statistics to solve public problems in areas such as disease control, disaster relief, urban planning, etc. should enter into partnerships to make this data available to government agencies and the public without charge, in fully anonymized form and subject to robust privacy protections. 7. Enact

legal and political reforms to create more open, transparent and participatory governance: Open government data cannot do its job in an environment of secrecy, fear and repression. Creating and defending open and participatory forms of governance is an ongoing challenge that requires constant work, scrutiny and engagement and there is no country that can claim to have perfected it. Governments should uphold basic rights to freedom of expression, information and association, and implement robust safeguards for personal privacy, as outlined in the UN Covenant on Civil and Political Rights. In addition, in line with their commitments in the UN Millennium Declaration (2000) and the Declaration of the Open Government Partnership (2011), they should take concrete steps to tackle gaps in participation, inclusion, integrity and transparency in governance, creating momentum and legitimacy for reform through public dialogue and consensus.

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ANNEX B: SDI4APPS SCENARIO TEMPLATES178 Use Case Template Use Case ID: Use Case Name: Created By:

Last Updated By:

Date Created:

Date Updated:

Last

Actors: Abstract: Description: Preconditions: Postconditions: Name of Input Dataset: Name of Output Dataset: Name of the Application Front-end Facilities Frequency of Use: Existing Tool: Development Type: Normal Course of Events: Exceptions: Includes: Special Requirements: Assumptions: Notes and Issues:

Guidance for Use Case Template This template has the aim of collecting use cases for the SDI4Apps project reflecting identified requirements and with the objective of satisfying the needs of use cases in 178 Adapted from SmartOpenData, D2.2 “User Requirements and Use Cases”, April 2014, available at www.smartopendata.eu/public-deliverables, in line with the SDI4Apps social validation methodology described in sections 2 and 3. Page 140 of 156



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terms of SDI4Apps infrastructure framework (data modelling and linked open data (LOD) alignment, semantic front-end facilities, target pilots, including quality and functionalities provided).

Use Case Identification Use Case ID Each use case is given a unique numeric identifier, in hierarchical form as follows: UC.Beneficiary number.Use Case Number. Example: UC.15.01 Related use cases can be grouped in the hierarchy. Functional requirements can be traced back to a labelled use case. Use Case Name State a concise, results-oriented name for the use case. These reflect the tasks the user needs to be able to accomplish using the system. Include an action verb and a noun.

Use Case History Created By Supply the name of the person who initially documented this use case. Date Created Enter the date on which the use case was initially documented. Last Updated By Supply the name of the person who performed the most recent update to the use case description. Date Last Updated Enter the date on which the use case was most recently updated.

Use Case Definition Actor An actor is a person or other entity external to the software system being specified who interacts with the system and performs use cases to accomplish tasks. Different actors often correspond to different user classes, or roles, identified from the customer community that will use the product. Name the actor(s) that will be performing this use case. In case of multiple actors, please describe mutual interaction and provide visual description via actor interaction diagram. This document reminds you that DoW has classified four target users •

Experts dealing with land use (including risk management) who will use the framework and collected data for their advanced analyses and data processing and also for publication and promotion of their research and other activities.

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Public (citizens, educators, NGOs...) that will have an opportunity to find new and interesting information about marginal European regions. They will also have a chance to publish their data and participate in decision making.

•

Business subjects in regions with cultural landscapes. They will use the framework to support their business activities connected with tourism, transport or health care.

•

Policy makers, including local and regional authorities, protected areas administrations, national heritage institutions or environment protection institutions and EC DGs.

Therefore, the Actors should be classified inside these groups. Abstract A condensed use case overview summarizing addressed content and functionality. Abstract should be kept under 120 words. Description Provide narrative description of the reason for and outcome of this use case, or a highlevel description of the sequence of actions and the outcome of executing the use case. Preconditions List any activities that must take place, or any conditions that must be true, before the use case can be started. Number each precondition. Example: 1. User’s identity has been authenticated. 2. External source of Data must be linked Postconditions Describe the state of the system at the conclusion of the use case execution. Number each postcondition. Example: 1. Visualization of maps. 2. Data updated in a database. 3. Generation of a report Name of the input Dataset If the use case writes a dataset or has a dataset as an input, this section shows its name (or names). The dataset will be depicted using the Dataset Template, available below. Name of the output Dataset If the use case will generate a dataset or will influence creation of new dataset as an output, this section shows its name (or names). The dataset will be depicted using the Dataset Template, available below. Name of the Application

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If the use case will require the development of an application this section shows its name (or names). The Application will be depicted using the Application Template, available below. Front-end Facilities Please state which SDI4Apps Front-end Facilities are going to be addressed with the use case: Choose one or more of the following options: • • •

Semantic indexing infrastructure, Visualisation framework, Notification service.

Frequency of Use Estimate the number of times this use case will be performed by the actors per some appropriate unit of time. Existing Tool Are there exiting tools that already implement your Use Case? If they exist, the name and information URL should be included. Development Type Indicate the approach that the use case will be deployed with. Chose from: • New. SDI4Apps has to develop this tool • Recycle. SDI4Apps has to adapt an existing tool • Paste. SDI4Apps could re-use an existing tool (considering relevant Intellectual Property Rights (IPR)) Normal Course of Events

directly

Provide a detailed description of the user actions and system responses that will take place during execution of the use case under normal, expected conditions. This dialog sequence will ultimately lead to accomplishing the goal stated in the use case name and description. This description may be written as an answer to the hypothetical question, “How do I ?” This is best done as a numbered list of actions performed by the actor, alternating with responses provided by the system. Exceptions Describe any anticipated error conditions that could occur during execution of the use case, and define how the system is to respond to those conditions. Also, describe how the system is to respond if the use case execution fails for some unanticipated reason. Number each exception using the Use Case ID as a prefix, followed by “EX” to indicate “Exception”. Example: UC.15.01;EX.1. Includes List any other use cases that are included (“called”) by this use case. Common functionality that appears in multiple use cases can be split out into a separate use case that is included by the ones that need that common functionality. Special Requirements Identify any additional requirements, such as non-functional requirements, for the use case that may need to be addressed during design or implementation. These may include performance requirements or other quality attributes. Page 143 of 156



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User Validation How the scenario will be user validated, choose all that apply from: 1. User Engagement 2. Direct user interaction with open data access processes 3. Co-design of innovative “demand pull” services

Criteria of Success of the Scenario Provide a short description of the scenario’s community(ies) criteria of success for the pilot. Expected interoperation with the other SDI4Apps pilots Choose from the list of SDI4Apps Pilots: P1- Easy Data Access P2 - Open Smart Tourist Data P3 - Open Sensor Network P4 - Open Land Use Map Through VGI P5 - Open INSPIRE4Youth P6 - Ecosystem Services Evaluation SDI4Apps Cloud Service Model required Estimate which SDI4Apps Cloud Service Model the Scenario will mainly require. Choose from the following 179 1. Applications – Software as a Service - SaaS 2. Platform as a Service - PaaS 3. Infrastructure as a Service - IaaS SDI4Apps Enabler Functions required Briefly described the SDI4Apps Generic and Specific Enabler Functions 180 that you expect the Scenario will require. Assumptions List any assumptions that were made in the analysis that led to accepting this use case into the product description and writing the use case description. Notes and Issues List any additional comments about this use case or any remaining open issues or TBDs (To Be Determined) that must be resolved. Identify who will resolve each issue, the due date, and what the resolution ultimately is.

Dataset Template Dataset ID: Dataset Name: Created By:

Last Updated By:

Date Created:

Date

Last

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Updated: Dataset description: Dataset type: Availability: Format& Storage: Size: Openness: LOD Status: LOD Functionality Description: Access Rights:

Guidance for Datasets Template The following template has the aim of collecting the information about the datasets that will be used in order to implement the SDI4Apps Use Cases. If a SDI4Apps use case refers to a dataset, either as input or as output, it is mandatory to create a Dataset report using the following template.

Dataset Identification Dataset ID Give each dataset a unique numeric identifier, in hierarchical form as follows UC.Beneficiary number.Use Case DS.Number.Dataset number. Example: UC.15.01;DS.01 Dataset Name State a concise name for the Dataset.

Dataset History Created By Supply the name of the person who initially documented this dataset. Date Created Enter the date on which the dataset was initially documented. Last Updated By Supply the name of the person who performed the most recent update to the dataset description. Date Last Updated Enter the date on which the dataset was most recently updated.

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Datasets information Dataset description Provide short narrative dataset description. Dataset type Defines, whether the dataset is of input or output type. Availability This section will answer the following questions: • Does the dataset already exists? • Is the dataset already available, visible and public? Format & Storage Format (encoding) of the dataset (supported files extensions: • File encodings: ESRI Shapefile, GML, GeoTiff, JPEG 2000… • Application interface allowing access to dataset: WxS (WFS, WMS, WMTS), RESTful, GeoSPARQL… Any other typeCurrent dataset storage: • Relational Database: SQLite, Oracle, PostGis… • Semantic triple storage: Virtuoso,Strabon…. Size How large is the Dataset / Database? If the previous question has no sense because the data are not available directly, the question could be: How large is the information obtained from the database or service? Order of magnitude: bytes, Kbytes, etc… Openness What is the level of openness of dataset based on 5 ★ Open Data classification 181? LOD Status Do the datasets need to be linked or is the dataset semantically self contained? If the datasets have to be linked, the following question is: What other datasets could it link with? LOD Functionality Description What operations are needed on the data? Some answers could be: • Transformation (CSV -> RDF, relational data -> RDF, etc) • Storage • Search • Federated querying • Visualization Access Rights Does the dataset come with the licence? If so, what type? Is the dataset public? Is it free? Allowed Operations: 181 http://5stardata.info/ Page 146 of 156


D2.2 Social Validation Methodology 621129) • • • •

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Read Write Modification Scripts execution

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Application Template Application ID: Application Name: Created By:

Last Updated By:

Date Created:

Date Updated:

Last

Application description: Availability: Format: Supported functionality / capabilities:

Guidance for Application Template The following template has the aim of collecting the information about the applications and their interfaces that will be deployed in order to implement the SDI4Apps use cases. Name of the Application, it is mandatory to define an Application interface using the following template.

Application Identification Application ID Provide with each application interface an unique numeric identifier as follows UC.Beneficiary number.Use Case AI.Number.Dataset number. Example: UC.15.01;AI.01 Application Name State a concise name for the Application.

Application History Created By Supply the name of the person who initially documented this application interface. Date Created Enter the date on which the application interface was initially documented. Last Updated By Supply the name of the person who performed the most recent update to the application interface description. Date Last Updated Enter the date on which the application interface was most recently updated.

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Application information Application description Provide short narrative application interface description. Availability This section will answer the following questions: •

Does the application interface already exist?

•

If so, is it already available, visible and public?

Format Possible instance of application interface: •

Graphical user interface

•

Machine readable interface

•

Other interface

Supported functionality / capabilities What kind of functionality does the application interface support?

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ANNEX C: Draft Workshops Aiming at

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Agenda

Generating a stakeholders

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Stakeholder with/by

What is SDI4Apps? • Presentation of SDI4Apps • Central focus of SDI4Apps: Social validation process • Presentation of initial analysis of stakeholders: Who are they? • Motivation on why to move from participation to involvement: initial introduction of potential associated benefits

Warm-up Session

(Grant

Keeping in mind achievements towards success DoW D2.3.1/2/3 Internal Validation Reports Y1/2/3 D2.4.1/2 External Validation Report – Y2/3

What is SDI, GI, OD, LOD and why are they relevant to you?  What are the expected benefits of the SDI4Apps Platform for your organization?  What do you think are the Platform benefits for the community?  And how about the combined benefits with SDI4Apps in the pilot? Structured Presentations from the participants With supporting material

Key Session on technical aspects: Aimed at participants who may become involved and to those identified as users/service providers/App developers

Presentation of the profile of the pilot scenario • Current status (including local social network groups) • Data and metadata used • User scenarios defined • Tools used • Standards used • Who are the users? • What are the user’s requirements? • Identification of gaps from existing services • Potential improvements in availability, access and use • Potential benefits from the SDI4Apps platform services: advantages from a seamless and interoperable system of services to aggregated GI and OD.

Building on Section 5 and 6. Platform functionality. User feedback

Structured-interactive discussion by stakeholders on all the above issues - With supporting material.

Identification of SDI4Apps value-add with stakeholders

Rationale for use of the SDI4Apps platform at pilot level • Advantages associated with the co-design of apps and services targeted at user’s requirements • Discussion on current trends in technology • What is at stake: technology, services and data Page 150 of 156

Contributing to: D6.2 Initial Deployment of Single Pilot Platforms D6.3 Progress Report and Pilot Platforms Update



• • • • • • • • •

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accessible to regions. D6.4 Progress Report and The inter-linkages amongst the Final Pilot Platforms Release local/regional/national contexts Best/good practices in technological advances Bottlenecks of the process in technical/operational terms How the current policy environment enables or restricts data access, integration and use Identification of these policies - at what scale: local/regional/national/EU? How can SDI4Apps support better decisionmaking? What do stakeholders appreciate and recommend in terms of dissemination/awareness-raising and other mechanisms for user engagement Other pilots: potential for twinning/ sustainability/scaling-up issues What mechanisms to develop for this?

Structured-interactive discussion by stakeholders on all the above issues - With supporting material

Social validation in the context of SDI4Apps: Moving from practice to outcomes for impact

Impact Assessment  Identified gaps in the wide application of the different technological advances in INSPIRE and LOD. How has impact been assessed?  Innovation in terms of joint accountability of coordination/integration: co-designing evaluation of impact  In your opinion, how useful is the social validation?  Conceptual basics for the Social Validation: creating a critical mass of multi-stakeholder partnerships (different mechanisms within SDI4Apps: creation of local social networks/participating in other networks…  What should be the criteria for evaluating the impact of the SDI4Apps platform in the pilot?  How to quantify and qualify it?  Resulting benefits from feedback as part of the social validation: expectation of best case scenario  What are the ‘enabling’ elements of better decision-making?  What decision and policy framework and level of governance can be addressed by the integration of services/sharing data, etc.  Expected impact from the overall project?

Contributing to: D2.3.1/2/3 Internal Validation Report Y1/2/3

Structured-interactive discussion by stakeholders on all the above issues - With supporting material

Moving the agenda forward from participation to involvement

• • •

Listing of concrete user needs for common services, Contributing to: apps and tools for a wider use of GI, OD and LOD. D2.4.1/2 External Concrete identification of aggregation steps for the Validation Report – Y2/3 deployment of trans-European services Data sharing from pilots with validation of usefulness

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Users to identify requirements and services to be linked to international initiatives and data sources Mechanisms for a continuous interaction: groups/social networks

Note: User workshops should be comprehensive enough to address all of the above issues. It is well understood that more preparation may have to be devoted to some of the proposed sessions. This is to be gauged by the responsible partners who know best the level of development of the validation pilot at the time of each workshop. For example some of the stakeholders may or may not know what they should expect or how they should benefit from the project. From their interaction some views on the expected impact should emerge. Of course the moderator/partner must provide guidance to the discussions on know the potential that SDI4Apps may offer to the communities. This agenda only serves as a guidance for engaging into a coherent approach for the organization of the workshops. It is expected to be a key mechanism for demonstrating the application of the concepts behind the Living Lab/SSRI approach and thus of the Social Validation focus of the SDI4Apps project.

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ANNEX D: LIST OF ABBREVIATIONS API - Application Programming Interface CC - Creative Commons CLC - Corine Land Cover CMS - Content Management System Copernicus - the European Earth Observation Programme, used to be known as GMES CRS - Coordinate Reference System CSS - Cascading Style Sheets CSW - Catalogue Service for the Web DAE - Digital Agenda for Europe DBMS - DataBase Management System DCAT-AP - Data Catalogue vocabulary Application Profile DOW - SDI4Apps Description of Work, Annex I to the Grant Agreement. EC – European Commission EEA - European Environmental Agency ELF - European Location Framework ENISA - European Network and Information Security Agency ESS - Ecosystem services ETIS - European Tourism Indicators System EU – European Union FI - Future Internet FLOSS - Free/Libre and Open Source Software GA - SDI4Apps Grant Agreement. GeoJSON - Geographic JavaScript Object Notation GEOSS - Global Earth Observation System of Systems GI - Geospatial/Geographic Information GIS - Geographic/Geospatial Information Systems GLOD - Geospatial Linked Open Data. GMES - Global Monitoring for Environment and Security – now known as Copernicus GML – Geography Markup Language GPS - Global Positioning System HCI – Human Computer Interface HTML - Hypertext Markup Language IDE - Integrated Development Environment

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INSPIRE – INfrastructure for SPatial InfoRmation in Europe IOT - Internet of Things IPR - Intellectual Property Rights ISO – International Organisation for Standardisation ISO 19115 – ISO 19115:2003-Geographic Information Metadata ISO 19118 – ISO 19118 Geographic Information-Encoding ISO 19139 – ISO/TS 19139-Geographic Information-Metadata -XML schema implementation IT - Information technologies IU - Innovation Union JSON - JavaScript Object Notation KML – Keyhole Markup Language LBS - Location-based Services LLA - Living Lab Approach LOD - Linked Open Data LOGD – Linked Open Government Data MDA - Model Driven Architecture MDR - Metadata Registry of the EU Publications Office MT - Machine Translation MVC - Model View Controller MVP - Model View Presenter NGO - Non-Governmental Organisation NLP – Natural Language Processing OD - Open Data ODC - Open Data Commons OGC - Open Geospatial Consortium OSM - OpenStreetMap OWL - Web Ontology Language PaaS - Platform as a Service, PM - Person Month PPP - Public Private Partnership QA - Quality assurance QAPP - Quality Assurance Project Plan QC - Quality control QoS - Quality of Service RDBMS - Relational DataBase Management System RDF - Resource Description Framework Page 154 of 156



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RDFS - Resource Description Framework Schema REST - Representational State Transfer RL - Reference Laboratory ROI - Return on Investment RSS - Rich Site Summary (originally RDF Site Summary) SaaS - Software as a Service SDI – Spatial Data Infrastructure SDI4Apps – Uptake of Open Geographic Information through Innovative Services based on Linked Data SEIS – Shared Environmental Information System SISE - Single Information Space in Europe for the Environment SKOS - W3C Simple Knowledge Organization System SLA – Service Level Agreement SME - Small to Medium Enterprise 182 SOA – Service Oriented Architecture SOAP - Simple Object Access Protocol SPARQL - SPARQL Protocol and RDF Query Language SQL - Structured Query Language SQL/MM - SQL Multimedia and Application Packages (as defined by ISO 13249) SRID - Spatial Reference system IDentifier SRS - Spatial Reference System SSI - Social Spaces for Innovation SSRI - Social Spaces for Research and Innovation SVG - Scalable Vector Graphics SVI - Social Validation Indicator TRL - Technology Readiness Levels UDI - User Driven Innovation UI - User Interface UML - Unified Modelling Language URI – Uniform Resource Identifier URL - Uniform Resource Locator URM – Uniform Resource Management VGI - Volunteered Geographic Information W3C - World Wide Web Consortium 182 Defined by the European Commission at http://ec.europa.eu/enterprise/policies/sme/factsfigures-analysis/sme-definition/ Page 155 of 156



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WCS – Web Coverage Service WFS - Web Feature Service WMC – Web Map Context WMS - Web Map Services WPS – Web Processing Services WWW - World Wide Web XHTML - eXtensible HyperText Markup Language XML - eXtensible Markup Language

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