Towards Semantic Spatial Data Infrastructures: A framework for sustainable development Tatiana Delgado Fernández a, José Luis Capote Fernández b, National Commission of SDI in Cuba (CIDERC) Calle 4 No. 313 e/3ra y 5ta, Playa, La Habana, CP 11300, Cuba a
[email protected] b
[email protected] Abstract Next generations of SDI should be oriented to semantics in order to deal with user’s languages and requirements in a maximum level possible. Based on a new vision called “The Semantic Web”, inspired in the past decade by Tim Berners-Lee, inventor of the Web and current director of the World Wide Web Consortium (W3C), this paper defines Semantic Spatial Data Infrastructures (SSDI) by describing their main components and principles. SSDI services should be equipped to enable a machine to understand human language, but to reach this state, it is necessary to create not only suitable semantic services, but also user domains ontology into a general semantic oriented SDI framework. This paper demonstrates that in the user-driven SDI, beyond the need for a service-oriented infrastructure, there is a need to describe user context/domains (domain ontologies) and to translate them into logical ones, in order to match appropriately with the required services. This paper presents a Semantic SDI Framework for sustainable development as part of an ongoing research into the CYTED-project “Evaluating and strengthening Spatial Data Infrastructures for sustainable development in Latin-America and the Caribbean” (IDEDES-606PI0294). The Semantic SDI framework for sustainable development includes social, economic and environmental dimensions expressed by means of domain ontologies and conceptual maps. The DF-P-S-I-R framework, used in the Global Environmental Outlook (GEO) by UNEP, the ecosystem approach and other international sustainable development reference models were premises to conceptualize the SSDI framework for sustainable development. Finally, some more detailed ontological components of an environmental dimension are shown, as well as, a semantic services perspective proposal, necessary in a Semantic Spatial Data Infrastructure. Keywords: spatial data infrastructure, sustainable development, ontology, semantics, semantic Web
1.
INTRODUCTION
Spatial Data Infrastructures (SDI) have been evolving from their first data-centric expressions until one more recent generation based on process and rather pull by the demand. However, its usage is not in correspondence with its actual potentialities. One of the reasons of this sub-use is its poor orientation and customization to the environment and vocabulary of the users’ communities. Based on a new vision called “The Semantic Web”, inspired in the past decade by Tim Berners-Lee, inventor of the Web and current director of the World Wide Web Consortium (W3C), this paper defines Semantic Spatial Data Infrastructures (SSDI) by describing their main components and principles. The development of Semantic SDI is undertaken in the context of the current version of Internet. Today there are some core technologies that support the development of Internet application and must be taken in account. XML (Bray, 2004) and in general the use of structured Languages has been helpful in the data transport across the network and id widely used. Most of standard defining data transports are XML schema definition applied to specific domains. GML (Cox, 2003) is used to define geographic data, WSDL (WSDL, 2001) is used to describe a Web Service (Alonso, 2003) and many other examples can be outlined. Web Services are the support for the application methods interoperability. This technology has been developed and refined mainly oriented to e-business application but also defined for many other fields. In SDI the OGC and ISO has a lot of work standardizing the access to Geospatial Web Services, saying access to geospatial data and to geospatial processing services. Some standards have been developed to support Web Services. Universal Data Discovery Interface (UDDI) (UDDI, 2007), Simple Object Access Protocol (SOAP) (W3C, 2001), etc. Other important element is the Web Service Oriented Architecture (SOA) (W3C, 2004) that includes all the application logic, enabling a wide distribution. This paper is aimed to provide a Model of a Semantic SDI (SSDI) and an overview of its application in a Sustainable Development context, as a base of the construction of an effective Sustainable Development Spatial Data Infrastructure based on SSDI. The content of this paper is organized in 4 sections. The following section focuses on the role of semantics in the SDI historical development. Then there is a section dedicated to describe the Project CYTED IDEDES “Evaluation and strengthening of SDI for sustainable development in Latin-America and the Caribbean”, which is the support of this research. The next section is aimed to define a Semantic Spatial Data Infrastructure comparing its new behavior regarding the traditional SDI models. Finally, a framework of Semantic SDI for sustainable development is presented.
2.
THE EVOLUTION OF SDI AND THE ROLE OF SEMANTICS
The continuum of SDI development, shown in the figure 1, depicts the generations of SDI (Rajabifard, 2006). The contribution of this paper to the generational approach presented by Abbas Rajabifard is the discussion of the place of semantics in future SDI to deal to the user requirements and language in a maximum level possible. In this
sense, the role played by new semantics-based SDI to enable the society spatially in a coming virtual environment was added to the original schema. Figure 1. Role of Semantics in the continuum process of SDI development (adapted from Rajabifard 2006)
Beyond the need for a service-oriented infrastructure on which citizen and organizations can rely for the provision of required services, there is a need to describe the user context/domains to match appropriately with the services required. In general, the technology exists to create this virtual world, but this is not enough in itself without the sustained input from both data producers and users (Rajabifard, 2006). Neither is enough without the sustained input of knowledge and meanings of the user context in order to match appropriately the conceptual with logical and computational models. Semantic-based SDI should be equipped to enable a machine to understand human language, but to reach this state, it is necessary to create not only suitable semantic services, but also user domains ontology. The main contribution of this work is the definition of Semantic Spatial Data Infrastructures (SSDI) by means of a general Conceptual Model of a SSDI and its application in sustainable development. 3. PROJECT CYTED IDEDES 606AC0294 A group of Iberian-American countries (Argentina, Brazil, Chile, Colombia, Cuba, Spain, Mexico and Uruguay) represented by geographic institutes, research groups and enterprises, decided to integrate their efforts to evaluate and strengthen the Spatial Data Infrastructures at national and regional levels for sustainable development. To reach its objectives the project will develop new semantic-based spatial services to contribute to decision making process in Latin-American and the Caribbean countries.
This project entitled “Evaluation and strengthening of Spatial Data Infrastructures for sustainable development in Latin-America and the Caribbean” (IDEDES-606AC0294, 2005) was generated into the framework of a Regional Program for Science and Technology for the development (CYTED). The project is supported by a grant consisting of around of USD 45000 per year during a period of four years (2006-2009). A general functional framework of the IDEDES Project is shown in the figure 2. Figure 2. A general functional framework of CYTED IDEDES Project
3.1 Ontologies in IDEDES Project One of the core specific objectives of IDEDES is to build the necessary ontologies to make semantic the environment of an SDI. The figure 3 below shows the general ontology architecture defined by the Project IDEDES. Figure 3. Ontology Architecture in IDEDES
So far, two main tasks are being undertaken in the Domain Ontology Building into the IDEDES project: -
Determining the suitable methodologies according to the user scenarios: Some approaches have been analyzed regarding methodologies to create domain ontology. METHONTOLOGY, developed within the Ontological Engineering group at Universidad Politécnica de Madrid, is the most popular approach among IDEDES´s sustainable development groups, because it guides clearly in how to carry out the whole ontology development through the specification, the conceptualization, the formalization, the implementation and the maintenance of the ontology (Corcho et. Al., 2003). For instance, Hydrontology was created by the National Geographic Institute of Spain based on METHONTOLOGY. Another methodology is based mainly in the Noy and McGuinness approach complemented with a rigorous application of selected standards from ISO 1 9 1 0 0 familiy (Geographic Information/Geomatic) defended by the Universidad Agraria de La Habana (Balmaseda, 2006). One of the transversal problems in the methodologies studied is the poor handling of uncertainty and vagueness to define rules and some kinds of relationships.
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Creating ontology for each domain selected to impact in sustainable development. The first step in this sense was to create the context and the own semantic to sustainable development. To do that, several models of to Sustainable Development were used, such as Global Environmental Outlook from UNEP and other approaches from the UN Commission of Sustainable Development (CSD)
Beyond the construction of domain, upper, service and feature type ontologies, it is necessary the definition of a Semantic SDI Model to integrate these ontologies and the semantic services into the SDI environments. Next sections focus on the description of a Semantic Spatial Data Infrastructure Model and a framework for sustainable development. 3. SEMANTIC SPATIAL DATA INFRASTRUCTURE MODEL
Spatial Data Infrastructures represent a kind of complex infrastructures based on webs (network of networks based primarily on coordination rather than control). It could be classified according to the spectrum given by Edwards, P., et al, 2007 as a genuine infrastructure. SDI support ubiquitous, reliable, and widely shared geographical information resources operating on local, national and transnational scales. SDI as complex infrastructures should be modelled into multiple perspectives. A multiperspective approach to model SDI has been described using ISO Reference Model for Open Distributed Processing (RM-ODP) standard for several authors (Delgado, 2004; Delgado, 2005, Hjelmager, et al, 2005). Figure 4 shows a general schema of the description of an SDI by means of five perspectives, according to RM-ODP.
Figure 4. Modeling SDI with RM-ODP
Figure 4 depicts a traditional SDI rather identified with the two first generations shown in the continuum process of SDI development presented in Figure 1. Its model is based on the five perspectives of the Reference Model of Open Distributed Systems, and the taxonomy and elemental relationships are designed in correspondence with the level of abstraction suitable for the scope of this document. To adapt this SDI conceptual model to a new one oriented to Semantics, it was necessary to evaluate each component or perspective in order to find the possible implications of the semantics or knowledge in each one. The result is shown in the figure 5 in the Semantic Spatial Data Infrastructure Model. The main modifications from the original SDI ODP Model are highlighted in the schema of the figure 5. The following paragraphs will argue on the new elements, and changes.
Figure 5. Semantic Spatial Data Infrastructure Model
Beginning from the enterprise perspective, Semantic Spatial Data Infrastructures should include a new class to refer the domains to be semantically described. For instance, in the CYTED IDEDES Project context, the domains are related to sustainable development. Some examples in the environmental dimensions of sustainable development are water; atmosphere; land; oceans, seas and coasts and biodiversity. To describe knowledge and meanings involved with each domain, a new class or perspective has been added in the Semantic SDI Model. This perspective is marked up as Knowledge. Knowledge is then expressed by Domain Ontologies built by the domain’s experts. In order to get the understanding from the machine, a logical transformation of domain ontologies is necessary, so a new class of Logical Ontologies is included and expressed in the popular OWL (Web Ontology Language). Other modifications are necessary in other ODP perspectives of SDI. In the information perspective, data acquires a new meaning, because the catalogue and the metadata should manage and document, not only geographical data and services, but also the knowledge involved to the domain of the data. From the computational point of view, there are important aggregations corresponding with the necessary services, expressed by Semantic Queries, to enable a machine to understand human language. The engine to bridge domain and logical ontologies with the geographical data of an SDI is intended to be solved by means of Semantic Services. Some KD services and support tools (eg. Parsing, Fuzzy and other KD services) should be included in the Geographic Processing Services into the framework of a Semantic SDI.
A summary comparison between SDI ODP Model and Semantic SDI ODP model can be appreciated in the following figure 6: Figure 6. SDI Vs Semantic SDI Model
3.1 The computational perspective of a SSDI: Semantic Services To include semantics some tasks are necessary. First the knowledge must be included, so it is important to build ontologies as a media, not only to include the domain knowledge but to include de SDI specialist knowledge, modeling the better practice for Discovery, Composition and Invocation of Geospatial Web Services. Web Service Modeling Initiatives To make use of a Web service, a software agent needs a computer-interpretable description of the service, and the means by which it is accessed. An important goal for Semantic Web markup languages, then, is to establish a framework within which these descriptions are made and shared. Web sites should be able to employ a standard ontology, consisting of a set of basic classes and properties, for declaring and describing services, and the ontology structuring mechanisms of OWL provide an appropriate, Web-compatible representation language framework within which to do this.
Actually there are two main initiatives for modeling services in a first approach to Semantic Web Application. One of them is Web Service Modeling Ontology (WSMO). The Web Service Modeling Ontology (WSMO) is developed in the context of WSMO Working Group, as part of the SDK cluster, with the aim of, through alignment between key European research projects in the Semantic Web Service area, the further the development of Semantic Web Services and works toward further standardization in the area of Semantic Web Service languages and to work toward a common architecture and platform for Semantic Web Services. The WSMO Working Group includes the WSML Working Group, which aims at developing a language called Web Service Modeling Language (WSML) that formalizes the Web Service Modeling Ontology (WSMO), and the WSMX Working Group, which aims at providing an execution environment and a reference implementation for WSMO (Roman et al, 2005). The other initiative is Ontology Web Language for Service (OWL-S) (DAML, 2004). This describes a upper ontology for services, including its subontologies for profiles, processes, and groundings. The ontology is still evolving, and making connections to other development efforts, such as those building ontologies of time and resources. Sometimes OWL-S ontology is referenced as a language for describing services, reflecting the fact that it provides a standard vocabulary that can be used together with the other aspects of the OWL description language to create service descriptions. Semantic Services The figure 7 below depicts a disaggregating schema of the Semantic Services in a Semantic SDI.
Figure 7. Semantic Services in an SDI
Semantic Human Interaction Services
There are a set of services to enabling the interaction of human users with the Web, in this case with a SDI. These services must support the marshaling process between the user and provider knowledge. In the model proposed in this paper is significant the inclusion of the user knowledge in the provider knowledge using profiled open ontologies for store the definition of concepts extending domain ontologies available in the SDI knowledge base. Other important element is the semantic parsing of the user queries. User Knowledge Negotiation Service This service will provide the support for defining user specific concepts not included in the SDI Knowledge base. In the model of knowledge interoperability is important to match the terms in the user domain with the terms defined by the domain expert who develop the provider ontologies. The incomplete domains problem is intended to be solved with a profiled open ontology where the registered user can defined the terms not found in the provider extending existing ones. User Query Processing Service The natural language user query is useless for computing proposes. To make this query useful is important to build a structure denoting semantic elements on it. To do this the user query processing services will parse semantically the user input in order to obtain a taxonomic tree that represents the relation of the terms included and the role that plays in the query. Based on the facets that any concept has in the ontology (class, relation, property) this service generates a taxonomic tree, first approach to start the service discovery in a SDI. Semantic Management Service The Semantic Management Services are the core semantic services to support other higher level semantic services in a SDI. These services include the knowledge base services for annotation and similarity. Ontology Service An important group of Semantic Services are those oriented to support the consultation of ontology based knowledge bases. There exist some ontology services oriented to check similarity among concepts and to interact with the knowledge bases for querying and updating. There exist multiple tools that contemplated the participation of the users in the creation of ontologies, most of them using the Web environment. One of the most important is Ontolingua created in the University of Stanford. This tool provides a collaborative and distributed environment to explore, to create, to edit, to modify and to use ontologies. (Farquhar and Rice, 1997) Another tool is WebOnto that was developed by Knowledge Media Institute of the Open University (Open University). It was designed to support collective searches and creation and edition of ontology. It provides an interface of direct modification on screen of the ontological expressions and also a tool of debate on ontologies called Tadzebao, who can support synchronous and asynchronous debates about ontologies. (1Corcho and Gómez, 2003)
Semantic Web Service Annotation Service One of the most important elements considered in the initiatives for the web service modeling if the creation of semantic description of existing Web Services. This is the role of Semantic Web Service Annotation Service. There is a group working in semantic annotation for web services (SAWSDL) (W3C, 2007) and its work is strongly tied to the initiatives for web service modeling depicted above. The Web Services Description Language (WSDL) specifies a way to describe the abstract functionalities of a service and concretely how and where to invoke it. The WSDL 2.0 W3C Recommendation does not include semantics in the description of Web services. Therefore, two services can have similar descriptions while meaning totally different things, or they can have very different descriptions yet similar meaning. Resolving such ambiguities in Web services descriptions is an important step toward automating the discovery and composition of Web services — a key productivity enabler in many domains including business application integration. The Semantic Annotations for WSDL and XML Schema (W3C, 2007) (SAWSDL) W3C Recommendation defines mechanisms using which semantic annotations can be added to WSDL components. SAWSDL does not specify a language for representing the semantic models, e.g. ontologies. Instead, it provides mechanisms by which concepts from the semantic models that are defined either within or outside the WSDL document can be referenced from within WSDL components as annotations. These semantics when expressed in formal languages can help disambiguate the description of Web services during automatic discovery and composition of the Web services. Semantic Processing Service This group includes the services oriented to the semantic processing in a SDI. These services are intended to support the discovery, composition and execution of Web Services. These task are the most sensible to automate in order to provide a framework for the future development of the semantic Web. The figure 8 shows the sequence and evolution of semantic processing services. Figure 8. From user query to service invocation
Semantic Web Service Discovery Service This service involves automatically locating Web services that provide a particular service and that adhere to requested properties. A user might say, for example, “Find a service that sells airline tickets between San Francisco and Toronto and that accepts payment by Diner’s Club credit card.” Currently, a human must perform this task, first using a search engine to find a service and then either reading the Web page associated with that service or executing the service to see whether it adheres to the requested properties. With semantic markup of services, we can specify the information necessary for Web service discovery as computer-interpretable semantic markup at the service Web sites, and a service registry or (ontology-enhanced) search engine can automatically locate appropriate services. Semantic Web Service Composition Service Semantic web service composition service involves the automatic composition of appropriate Web services to perform some task, given a high-level description of the task’s objective. In the proposed model this task fallows discovery of appropriate web services that provide the data or web methods useful for the user goal. The output of this service must be a web service choreography formalized in a language like Web Service Choreography Language (WSCL) (W3C, 2004). Semantic Web Service Choreography invocation Service The end task for meet the user goal is the execution of the choreography obtained from the Semantic Web Service Composition Service. This is a hard task due to the complexity of spatial data. When the execution stage of choreography is a SDI then the size of the data may be big, suppose a feature collection or a raster image. Then the capabilities of the execution environment must be consider. One of them, currently developed is Web Services Execution Environment (WSMX). It has its foundation in the Web Service Modeling Ontology (WSMO) (Roman et al, 2005) and the Web Service Modelling Framework (WSMF) (Fensel and Bussler, 2002). The goal of WSMX is to
provide a flexible environment for application and business integration based on strongly decoupled physical components with strong mediation services enabling every party to speak with each other as advocated in WSMF. 4. SSDI: FRAMEWORK FOR SUSTAINABLE DEVELOPMENT There were two main starting points to develop a framework of SDI to sustainable in the IDEDES Project: 1. The three dimensions of sustainable development given by UN: social, economic and environmental dimensions. 2. The methodology of the Global Environmental Outlook (GEO) Assessments from the United Nations Environmental Program (UNEP, 2007). GEO 4 Assessment uses the drivers- pressures-states- impact- response (DPSIR) According to GEO, the concepts of human well-being and ecosystem services are core in the analysis, focusing on ecosystems to cover the entire environment and the interaction with society. As it is shown in the figure 9, in the framework of SDI for sustainable development, the environmental dimension is presented by means of the ecosystems and their involving with the pressures produced by drivers or fundamental processes in society, which drive activities with a direct impact on the environment (demographics; consumption and production patterns; scientific and technological innovation; economic demand, markets and trade; distribution patterns; institutional and social-political frameworks and value systems).
Figure 9. Framework of SDI for sustainable development
In the GEO framework, environmental State also includes trends, which often refers to environmental change. This change may be natural, human-induced or both (UNEP, 2007). For our own framework, to model these changes in a Semantic SDI, it is necessary to structure the knowledge with the complexity of the physical, chemical and biological systems constituting the environment. The expression of them in an SSDI for sustainable development is the basic domain ontologies for water, atmosphere, soil and biodiversity; as well as, ontologies of more complex ecosystems as forestry, mountains, coastal zones and hydrographic basin. In terms of Responses, they address issues of vulnerability of both people and the environment, and provide opportunities for reducing human vulnerability and enhancing human well-being (UNEP, 2007). One of the most important contributions of the IDEDES Project is the construction of ontologies o policies (responses) in order to convert the SSDI in an effective tool for decision making. Some examples of these ontologies of domains/responses which are being undertaken in the project are: -
Forestry Ordering Land Management Risk Management
CONCLUSIONS During two years, the researchers of the CYTED IDEDES Project have been working in the definition of a Semantic SDI for sustainable development. So far, there is a conceptual model of SSDI and a logical design of the semantic services needed to reduce the gap between producers/providers and users of an SDI.
A framework of SSDI for sustainable development is presented based on the GEO 4 Assessment methodology from UNEP. Fundamental focus is made in the environmental dimension on the semantic, not only of ecosystems, but also of policies/responses to provide opportunities to reduce human vulnerability and enhance human well-being. Future work should be addressed to impact in the following issues: -
Completing the ontology development for the sustainable development domains selected Definition of application scenarios at the regional, national and local levels, oriented to ecosystems management. Interrelation of domain ontologies according to the thematic definition in the selected scenarios. Creation of Core Ontologies or Upper ontologies to SDI contexts. Development of logical models e implementation of semantic services to be included into the SDI set of services. Implementing of Semantic SDI in the selected scenarios.
ACKNOWLEDGEMENT This paper has been supported by the Regional Program of Science and Technology for the Development (CYTED) with its project IDEDES 606AC0294 (2006-2009). Special gratefulness to Roberto Pérez de los Reyes for his support with GEO Assessment methodology. REFERENCES Alonso, G., Casati, F., Kuno, H., & Machiraju. Web services. s.l. : Springer, 2003. Bray, T., et al XML 1.0, Extensible Markup Language, World Wide Web Consortium Recommendation. [En línea] Octubre de 2004. http://www.w3.org/TR/2004/REC-xml20040204 . Corcho, O., M. F.-L., Gómez-Pérez, A., (2003). Methodologies, tools and languages for building ontologies. Where is their meeting point? Data & Knowledge Engineering, ELSEVIER. 46: 41–64. Cox, S, y otros. OpenGIS® Geography Markup Language (GML) Implementation Specification. s.l. : OpenGIS® Implementation Specification, 2003. OGC 02-023r4. DAML, 2004. OWL-based Web service ontology (OWL-S). . [online] 2004. http://www.daml.org/services/owl-s/1.1/. Delgado, T. 2005. Infraestructuras de Datos Espaciales en países de bajo desarrollo tecnológico. Implementación en Cuba. Tesis de doctorado, ITM, Comisión de Geodesia y Cartografía, 2005. Delgado, T. 2005. Evaluation and strengthening of Spatial Data Infrastructure for Sustainable Development in Latin-America and the Caribbean, IDEDES-606AC0294, CYTED, available in www.cyted.org. Edwards, P., Jackson, S., Bowker,G., Knobel, C., 2007, “Understanding Infrastructures: Dynamic, Tensions and Design”. Report of a Workshop on “History & Theory of infrastructure: Lessons for new scientific cyberinfrastructures”, NSF Grant 0630263.
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