Road Mapping Infrastructures for Advanced Visual Interfaces Supporting Big Data Applications in Virtual Research Environments Marco X. Bornschlegl
Andrea Manieri
Paul Walsh
University of Hagen Faculty of Mathematics and Computer Science 58097 Hagen, Germany marco-xaver.bornschlegl@ fernuni-hagen.de
Engineering Ingegneria Informatica SPA 00185 Rome, Italy
[email protected]
Cork Institute of Technology CIT Informatics Cork, Ireland
[email protected]
Tiziana Catarci
Matthias L. Hemmje
Sapienza - Univ. di Roma Dipartimento di Ingegneria Informatica, Automatica e Gestionale ”A.Ruberti“ 00185 Roma, Italy
[email protected]
University of Hagen Faculty of Mathematics and Computer Science 58097 Hagen, Germany matthias.hemmje@ fernuni-hagen.de
ABSTRACT
Keywords
Handling the complexity of relevant data requires new techniques about data access, visualization, perception, and interaction for innovative and successful strategies. In order to address human-computer interaction, cognitive efficiency, and interoperability problems, a generic information visualization, user empowerment, as well as service integration and mediation approach based on the existing state-of-the-art in the relevant areas of computer science has to be achieved. This workshop will address these issues with a special focus on supporting distributed Big Data analysis in Virtual Research Environments (VREs). In this way, the overall scope and goal of the workshop is to bring together researchers in these areas to achieve a road map, which can support the acceleration in research activities by means of transforming, enriching, and deploying advanced visual user interfaces for managing and using e-Science infrastructures. Advancements in this fields of research can i.e. support the, creation, configuration, management, and usage of distributed Big Data analysis in VREs.
Virtual Research Environments, Advanced Visual User Interfaces, Distributed Big Data Analysis, Information Visualization, User Empowerment
CCS Concepts •Human-centered computing → HCI theory, concepts and models;
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).
AVI ’16 June 07-10, 2016, Bari, Italy c 2016 Copyright held by the owner/author(s).
ACM ISBN 978-1-4503-4131-8/16/06. DOI: http://dx.doi.org/10.1145/2909132.2927471
1.
INTRODUCTION AND MOTIVATION
The availability of data has changed dramatically over the past ten years. The wide distribution of web-enabled mobile devices and the evolution of web 2.0 technologies are contributing to a large amount of data (so-called Big Data) [3]. Usable access to complex and large amounts of data poses, e.g., an immense challenge for current solutions in, e.g., business analytics. Handling the complexity of relevant data (generated through information deluge and being targeted with Big Data technologies) requires new techniques about data access, visualization, perception, and interaction for innovative and successful strategies. As a consequence research communities as well as industry, but especially research teams at small universities and Small and Medium-sized Enterprises (SMEs), will be faced with enormous challenges. Furthermore, current e-Science research resources and infrastructures (i.e., data, tools, and related Information and Communication Technology (ICT) services) are often confined to computer science expert usage only and fail to leverage the abundant opportunities that distributed, dynamic, and eventually interdisciplinary Virtual Research Environments (VREs) can provide to scientists, industrial research users as well as to learners in computer science, data science and related educational environments. The scientific resources like other infrastructures is influenced by globalization. Scientists have been both motivated and enabled to work across disciplinary and international borders by technological advances beyond geographical or
institutional boundaries [5]. This trend calls for innovative, dynamic and ubiquitous research supporting VREs where scattered scientists can seamlessly access data, software, and processing resources managed by diverse systems in separate administration domains through their web browser [1]. Therefore, nowadays a VRE allows multiple researchers in different locations to work together in real time without restrictions as it was, e.g., already very early described by UK’s Joint Information Systems Committee (JISC) VRE Collaborative Landscape Study in 2010 [2] as ”a platform, to help researchers from all disciplines to work collaboratively by managing the increasingly complex range of tasks involved in carrying out research on both small and large scales“ [4, 2]. The purpose of this research road-mapping workshop is threefold. Firstly, it aims to consolidate information, technical details, and research directions from the diverse range of academic and industrial R&D projects currently available. Secondly, based on visions of future infrastructures, gaps in the current state of the art will be determinated and thirdly, new areas of research, which require fund and support along with new areas for collaboration outside, will be identified. The aim of this workshop is to bring together researchers and practitioners who are able to contribute to and aid in the development of a research road map. This road map can be used to inform, influence and disseminate ideas to founders, the wider research community, and the general public. Based on submitted position papers and existing research it will describe the current baseline of infrastructures for advanced visual user interfaces supporting Big Data applications in VREs. Furthermore, it will describe research gaps that need to be filled for archiving our research and development ambitions. Achievement of the goal of the workshop is supported by the presentation and discussion of research aiming at delivering Advanced Visual User Interfaces for VREs, e.g., supporting researchers and organizations in applying and maintaining distributed (spatially, physically, as well as potentially cross-domain) research resources for Big Data Analysis. These user interfaces can e.g. provide a basis for managing access to VRE features and services through open standards and they can be materialized through an open architecture and components derived from state-of-the-art research results being able to deal with Big Data resources and services at scale. The workshop will aim at delivering a road map covering a comprehensive set of standards-based services, visual user interfaces, and tools that support the complete life cycle of VREs in a domain agnostic fashion. A clear research, education and training agenda will be articulated that tracks and builds upon existing and emerging technologies and that respond to future visions of advanced visual interface infrastructures supporting Big Data applications in virtual research environments. The process will develop a baseline by drawing upon all of our previous workshops and other activities within our recent research projects and will produce a road map for research, technology and development. During the workshop future visions and a gap analysis will be mapped out. By treating this over the course of the day we can provide feedback to refine the baseline (to be captured in a workshop report and corresponding publications) and real research, technology and development gaps, which will be detailed in the road map. For this workshop idealization, knowledge capturing
road mapping approaches and activities developed during the EU FP7 projects INNOVANET, APARSEN, SCIDIPES, and the H2020 projects EDISON, SENSECARE and METAPLAT will be adopted. The overall scope and goal of the workshop is to achieve a road map, which can support the acceleration in research, education and training activities by means of transforming, enriching, and deploying advanced visual user interfaces for managing and using eScience infrastructures in VREs. In this way, the research, education and training road map will pave the way towards establishing an infrastructure for a visual user interface tool suite supporting VRE platforms that can host Big Data analysis and corresponding research activities sharing distributed research resources (i.e., data, tools, and services) by adopting common existing open standards for access, analysis and visualization. Thereby, this research helps realizing a ubiquitous collaborative workspace for researchers which is able to facilitate the research process and its Big Data Analysis applications.
2.
WORKSHOP PLAN
The workshop will be for a full day and structured to provide maximum time for group discussion and brainstorming in the following key issues: • Advanced Visual User Interfaces supporting Big Data Collection, Curation and Archival • Advanced Visual User Interfaces supporting Big Data Visual Analytics • Advanced Visual User Interfaces supporting Big Data Modeling, Structuring, Knowledge Extraction and Semantic Annotation • Advanced Visual User Interfaces supporting Big Data Information Visualization and Interaction • Advanced Visual User Interfaces supporting Configuration and Management of Big Data Storage and Compute Infrastructures, Services, and Tools • Advanced Visual User Interfaces supporting Visual Mapping of Big Data to Visual Structures • Advanced Visual User Interfaces supporting View Transformations on Big Data Visual Structures • Advanced Visual User Interfaces supporting User Empowerment and Meta Design in Big Data Applications The workshop is structured in four sessions. In the first session the participants are briefly introduce themselves with short 5 min talks. Following this the workshop are having a series of invited industry and eScience-infrastructure community perspectives. In the second session a gap analysis will be completed and in the third session the group is divided into sub-groups moderated by the workshop organizers to have focused discussions on some of the key gaps identified earlier. In the fourth session the group is reconvened to summarize the gaps and set forth time line and areas for new research. The workshop ens with a detailed discussion to define immediate next steps for completing the road map document.
3.
ORGANIZERS BACKGROUND
Marco X. Bornschlegl is PhD Student at the University of Hagen (FernUniversit¨ at in Hagen FUH). He has several years experience in different IT positions and various national and international IT infrastructure projects within a large international engineering and services group, which develops, builds, maintains and operates facilities and structures for the industrial, energy and real-estate sectors. Since 2014, he leads the Department Server Rooms, Integration and Performance Management. He received his B.Sc. degree in Applied Computer Science and M.Sc. degree in Information Technology at the Mannheim University of Applied Sciences and was a Fellow in the Klaus Murmann Fellowship Programme of the Foundation of German Business (sdw), which is directed toward outstanding, socially committed students and doctoral candidates who exhibit potential for taking on leadership responsibilities in business and society, until successful completion of his studies. Furthermore he received two additional scholarships (Mannheim Model Mid-Tier Industry Scholarship), from leading companies in the metropolitan area Rhein-Neckar. He completed his Bachelor and Master studies with honors and for his Master Thesis he received an award from a leading German Engineering Association (IfKom e.V.). Tiziana Catarci is full professor in Engineering in Computer Science and director of the ECONA research centre. During 2010-14 she has been UNIROMA1 vice-rector for technologies and infrastructures. Her main research interests are in theoretical and user oriented aspects of information access, user interfaces, usability, digital libraries, elearning, cooperative information systems, and data management. On these topics she has published over 200 papers in international journals, conferences and workshop proceedings, and 20 books. Tiziana Catarci and her group have been among the first in Italy to work on HCI, both from a theoretical and from an experimental point of view, and to introduce the HCI course in curriculum of UNIROMA1. In 2008, she has been the Co-chair of the 2008 edition of the largest and most important conference on humancomputer interaction, ACM CHI. With respect to applications, she has led or participated in various national and international projects on the above topics. In particular, she had recently successfully lead the WORKPAD project (FP6), developing a complete system running on mobile devices for emergency management, and the human-computer interaction part of the SM4All project (FP7), developing a smart home being universally accessible. Matthias L. Hemmje is full professor at the University of Hagen (FernUniversit¨ at in Hagen FUH), one of the leading distance universities in Germany. He is involved in FUH’s research clusters on Virtual Information and Knowledge Environments, Technology Enhanced Learning and E-Education, Knowledge-based Virtual Collaboration Environments, as well as Long term Archival and Digital Preservation. He has 20 years of experience in IT R&D on national and international level, has been author and co-author in more than 100 publications, is consulting as Senior Expert Consultant for the German Ministry for Research and Education (BMBF), the European Commission (EC), the German Research Foundation (DFG), and several R&D spin-offs. Ear-
lier affiliations include 15 years at the German National Research Center of Computer Science (GMD) and Fraunhofer Integrated Publication and Information Systems Institute (FhI IPSI) in Darmstadt, as well as University Professorships at Ludwig-Maximilians-University in Munich and University of Duisburg. With respect to applications, he has led or participated in leading functions in various national and international projects on the above R&D topics. In particular, he had successfully lead and is still leading relevant R&D activities within several EU projects including research activities on user interfaces, usability, information visualization, information access, archival, preservation, innovation road-mapping, big data and visual analytics, e.g., in the H2020 projects SENSECARE, METAPLAT, EDISON, RAGE as well as FP7 projects SCIDIP-ES, APARSEN, SMART VORTEX, as well as FP6 projects VIKEF, FAIRWIS, FAIRSNET, INNOVANET, FADIVA. Andrea Manieri is graduated in Computer Science 1998, with a master thesis on object-oriented lambda calculus with prof. Emeritus C. Boehm. In 2000 he joined EU projects as Technical Manager in the ECOLNET, then in 2002 he was appointed as RTD Coordinator in Engisanita Spa, an Engineering Group company on Health Care market. On April 2003 he joined again the Engineering labs as responsible of development of new business on Grid Technology establishing a specific unit and contributing to several project in FP6/FP7 project until 2013. He was also Project Director of VENUS-C project (FP7 INFRA-261556) and ERINA+ support Action (FP7 INFRA-261550). His Distributed Computing Laboratory contributed to more than twenty FP6 and FP7 initiatives ranging from AAA in distributed environments, Test and quality assurance of distributed software, grid and cloud infrastructures, infrastructure security and legal compliance. He is trainer in the company Academy ”Enrico della Vall“ for the Cloud technologies. On Aug 2013 he left the Laboratory and he has been tasked to bring Research result into Company business offering, as Business Developer and Trainer. As such, in the new EC funding program H2020 is coordinating the Company initiatives in the LEIT (ICT and SPACE) and Excellent Science Pillars and designed the Cloud Computing courses at the Engineering Academy. Paul Walsh is a Research Fellow in the Cork Institute of Technology (CIT) and a Senior Visiting Research Fellow at the University of Edinburgh where he manages research in medical informatics and bio informatics. He holds a Ph. D., M.Sc. and B.Sc. Hons in Computer Science from the National University of Ireland and has a long list of publications including outstanding paper awards and has consulted on a wide range of projects ranging from start-up technology companies to managing projects for global corporations. He is funded under national and international research schemes such as EU FP7 and Horizon 2020 programmes where he oversees research in data analytics, machine learning and high performance computing. He is co-founder and CTO of NSilico Life Science, which develops analytical and visualization software for the life science sector. His current research focus is effective visualization for big data in the life science sector.
4.
PROGRAM COMMITTEE
Themis Athanassiadou, EGI.eu, the Netherlands; Marco X. Bornschlegl, University of Hagen, Germany; Adam Belloum, University of Amsterdam, the Netherlands; Paolo Buono, Universita degli Studi di Bari, Italy; Tiziana Catarci, Universita di Roma, Italy; M. Francesca Costabile, Universita degli Studi di Bari, Italy; Matthias L. Hemmje, University of Hagen, Germany; Boro Jakimovski, Ss. Cyril and Methodius University in Skopje, R. Macedonia; Michael Kaufmann, Lucerne University of Applied Sciences and Arts, Switzerland; Andrea Manieri, Engineering Ingegneria Informatica SPA, Italy; Massimo Mecella, Universita di Roma, Italy; Ruben Riestra, INMARK, Spain; Paul Walsh, Cork Institute of Technology, Ireland; Huiru Zheng, Ulster University, United Kingdom
5.
ACCEPTED PAPERS
Engineering Study of Tidal Stream Renewable Energy Generation and Visualization: Issues of Process Modeling and Implementation, J. Harrison1 , and J. O. Uhomoibhi1 . 1 Ulster University; Tidal stream energy has the potential to make a significant contribution to energy mix in the future. Accurate modeling and visualization of both tidal resource and array layout enhances understanding of in-stream tidal behavior leading to improvements in site identification and optimal positioning of individual turbines. A realistic representation of blade loading conditions will aid designers and manufacturers in creating more robust devices and improve survivability. The main barriers to large scale deployments of tidal arrays are the costs associated with manufacturing, installation and maintenance. Therefore, presently tidal energy is not competitive on cost with more established renewable technologies. The current position paper investigates and reports on resource modeling, site selection, selecting optimal array configurations and the design and manufacture of devices for tidal stream renewable energy generation. This is aimed at developing models to reliably simulate real conditions, enhance understanding of tidal processes, flow regimes and device survivability issues. SenseCare: Towards an Experimental Platform for Home-Based, Visualisation of Emotional States of People with Dementia, Felix Engel1 , Raymond Bond2 , Alfie Keary5 , Maurice Mulvenna2 , Paul Walsh3 , Zheng Huiru2 , Ulrich Kowohl4 , and Matthias L. Hemmje1 . 1 Research Institute for Telecommunication and Cooperation; 2 Ulster University; 3 NSilico Life Science; 4 University of Hagen, Faculty of Mathematics and Computer Science; 5 Cork Institute of Technology, CIT Informatics In this paper, the support and care of people with dementia in their own homes is explored. The paper sets out a framework-, to gather and analyze data in the homes of people with dementia. Basic requirements are explored towards development of the SenseCare platform stemming from application scenarios in which various data streams are created, processed, analyzed, visualized and stored for ad-hoc or later reuse. The framework will be realized as a platform based on open ICT standards, implemented within the EC co funded SenseCare project. In this publication the components of the SenseCare platform are described, including the visualization of data.
Modern Technologies to Synchronize Data Sources and Information Visualizations, Christian Danowski1 , Marco X. Bornschlegl1 , Benno Schmidt2 , and Matthias L. Hemmje1 . 1 University of Hagen, Faculty of Mathematics and Computer Science; 2 Bochum University of Applied Sciences, Department of Geodesy. There are many systems that visualize abstract data in the context of information visualization (IVIS). However, most systems create unidirectional visualizations that represent a static product of the source data. Any changes to the content of the visualization - if that is possible at all - has no effect on the source data. This paper recommends an approach to use modern Web technologies and state-of-the-art system architectures to develop a bidirectional IVIS system where the client-user is able to alter data properties within three-dimensional visualizations (using the ISO-specified X3D format of the Web3D Consortium) that in consequence are automatically applied to the server-side data sources. Furthermore, relevant data changes on the server side are published to all registered clients to maintain a permanent consistent state. Particularly, a mediatorwrapper architecture is used in order to semantically integrate heterogeneous data sources in Big Data scenarios. Towards a Reference Model for Advanced Visual Interfaces Supporting Big Data Analysis, Marco X. Bornschlegl1 , Kevin Berwind1 , Michael Kaufmann2 , Felix C. Engel1 , Paul Walsh3 , and Matthias L. Hemmje1 . 1 University of Hagen, Faculty of Mathematics and Computer Science; 2 Lucerne University of Applied Sciences and Arts, School of Engineering and Architecture; 3 Cork Institute of Technology, CIT Informatics. This paper introduces an approach to develop an up-todate reference model that can support advanced visual user interfaces for distributed Big Data analysis in virtual labs to be used in e-Science, industrial research, and data science education. The paper introduces and motivates the current situation in this application area as a basis for a corresponding problem statement that is utilized to derived goals and objectives of the approach. Furthermore, the relevant state-of-the-art is revisited and remaining challenges are identified. An exemplar set of use cases, corresponding user stereotypes as well as a conceptual design model to address these challenges is introduced. The scenario and user stereotypes have been an expert roundtable. A corresponding architectural system model is suggested as a conceptual reference architecture to support proof-of-concept implementations as well as to support interoperability in distributed infrastructures. Conclusions and an outlook on future work complete the paper. A Meta-Design Approach to Support Information Access and Manipulation in Virtual Research Environments, Carmelo Ardito1 , Paolo Buono1 , M. Francesca Costabile1 , Giuseppe Desolda1 , and Maristella Matera2 . 1 Univ. di Bari Aldo Moro; 2 DEIB, Politecnico di Milano. Virtual Research Environments (VREs). i.e., distributed and dynamic environments that foster the collaboration of researchers from different disciplines by supporting the accomplishment of complex research tasks, lack efficient and effective user interfaces addressing user diversity. In this paper we illustrate the meta-design approach adopted in the
last years to design user interfaces adequate for different user communities: This approach is in particular suitable to address the variety arising in the cultural background of users, their reasoning strategies, the way they carry out their tasks in their daily practices, the languages and notations they are familiar with. We also describe a mashup platform, developed on the basis of a meta-design model, that enables end users to extract contents from heterogeneous sources and manipulate such content in their personal interactive environments, thus creating new content that can be shared among people collaborating to a certain task. Cost Effective Visualization of Research Data for Cognitive Development Using Mobile Augmented Reality, C. Onime1 , and J. O. Uhomoibhi2 . 1 The Abdus Salam International Centre for Theoretical Physics (ICTP); 2 Ulster University. In many Fields of scientific research, the numerical output of research work require proper interpretation in relation to real world situations. Graphical visualization is often used to ensure better comprehension of data (research outputs) by researchers, learners and other stakeholders. However, In the modern era, large scale experimentation as well as computer based simulations are generating massive amounts of numeric data that are almost impossible to visualize using traditional plots and graphs as they are limited in both dimensions and scale. Video has gained increasing popularity for presenting data due to its ability to convey motion and time. While, such video presentations are undoubtedly useful, they provide limited contributions to cognitive development. In this short paper, a cost effective use of mobile augmented reality in the visualization of scientific research data highlighting two use-cases that show the Three Dimensional (3D) semi-immersive and interactive environment in both educational and non-educational contexts, will be examined. Visual Analytics and Mining over Big Data. Discussing Some Issues and Challenges, and Presenting a few Experiences, Marco Angelini, Tiziana Catarci, Massimo Mecella, and Giuseppe Santucci. 1 Sapienza Universita di Roma, Dipartimento di Ingegneria Informatica Automatica e Gestionale; In this short position paper, we present a few concrete experiences of Visual Analytics over big data; as our experiences have been gained on the application domains of cyber security and OSINT, which are very relevant and crucial domains targets of possible VREs, we also discuss and propose an high-level reference architecture and pipeline for a Big Data service in VREs dealing with such aspects, in which the VA part is crucial in order to provide effectiveness trousers. Towards Interactive Visualization of Results from Domain Specific Text Analytics, Tobias Swoboda1 , Christian Nawroth1 , and Michael Kaufmann2 . 1 University of Hagen, Faculty of Mathematics and Computer Science; 2 Lucerne University of Applied Sciences and Arts, School of Engineering and Architecture. In Big Data analytics, visualization and access are central for the creation of knowledge and value from data. Interactive visualizations of analysis of structured data are commonplace. In this paper, information visualization and
interaction for the text analysis is addressed. The paper motivates this issue from a data usage standpoint, presents a survey of approaches in the area of interactive visualization of text analytics, and presents our proposal of a specific solution design for visual interaction with results from a combination of named entity recognition (NER) and text categorization (TC). This matrix-based model illustrates abstract views on complex relationships between abstract entities and is exemplary for any combination of feature extraction and TC. The aim of our example is to support feature extraction and TC researchers in distributed virtual research environments by providing intuitive visual interfaces. Rapidly Visualizing NGS Cancer Data Sets with Cloud Computing, Paul Walsh1 , Brendan Lawlor1 , Brian Kelly1 , Michael Bekaert1 , Timmy Manning1 , Timm Heuss1 , Xiangwu Lu1 , Roy Sleator1 , and Markus Leopold2 . 1 NSilico Life Science; 2 Darmstadt University of Applied Sciences. With the advent of NGS technology, clinical data sets now contain enormous amounts of valuable genomic information related to a wide range of diseases such as cancer. This data needs to be analyzed, managed, stored, visualized and integrated in order to be clinically useful. However, many clinicians and researchers, who need to interpret these data sets, are non-specialists in the IT domain and so need systems that are effective and easy to use. Herein, we present an overview of a novel cloud computing based NGS research management software system which has simplicity, scalability, speed and reproducibility at its core. The efficacy of the system is demonstrated by showing how the system enables rapid visualization of big data cancer sets. We present results from a bio-informatics pipeline run by SimplicityTM in Sage-Care, an EU funded cancer research project, for comprehensive genome mapping analysis and visualization.
6.
ACKNOWLEDGMENTS & DISCLAIMER
This workshop has been produced in the context of the EDISON project. The project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 675419. However, this workshop reflects only the author’s view and the European Commission is not responsible for any use that may be made of the information it contains.
7.
REFERENCES
[1] L. Candela. Virtual research environments. Technical report, Networked Multimedia Information System Laboratory, Italian National Research Council, 2011. [2] A. Carusi and T. Reimer. Virtual research environment collaborative landscape study. JISC, Bristol, page 106, 2010. [3] J. Freiknecht. Big Data in der Praxis. Carl Hanser Verlag GmbH & Co. KG, M¨ unchen, Deutschland, 2014. [4] Helmholtz-Gemeinschaft. Definition: Virtual research environments. http://www.allianzinitiative.de/en/ core activities/virtual research environments/definition, Feb 2011. Accessed: 2016-01-11. [5] J. Wilsdon et al. Knowledge, networks and nations: Global scientific collaboration in the 21st century. The Royal Society, 2011.
