Linked Data Visualization - Techniques, Tools, and Big Data

Linked Data (LD) is a well-established standard for publishing and managing structured information on the Web, gathering and bridging together knowledge from different scientific and commercial domains. The development of Linked Data Visualization techniques and tools has been followed as the primary means for the analysis of this vast amount of information by data scientists, domain experts, business users, and citizens.
This book covers a wide spectrum of visualization issues, providing an overview of the recent advances in this area, focusing on techniques, tools, and use cases of visualization and visual analysis of LD. It presents the basic concepts related to data visualization and the LD technologies, the techniques employed for data visualization based on the characteristics of data techniques for Big Data visualization, use tools and use cases in the LD context, and finally a thorough assessment of the usability of these tools under different scenarios.
The purpose of this book is to offer a complete guide to the evolution of LD visualization for interested readers from any background and to empower them to get started with the visual analysis of such data. This book can serve as a course textbook or a primer for all those interested in LD and data visualization.

List of contents

Preface.- Acknowledgments.- Introduction.- Principles of Data Visualization.- Linked Data Visualization Tools.- Visualization Use Cases.- Empirical Evaluation of Linked Data Visualization Tools.- Conclusions and Future Challenges.- Bibliography.- Authors' Biographies.

About the author

Laura Po is an Associate Professor in the "Enzo Ferrari" Engineering Department at the University of Modena and Reggio Emilia, Italy. She obtained a Ph.D. in Computer Engineering and Science from the University of Modena and Reggio Emilia in 2009. She has given several tutorials at ISWC Conference in 2018 and at the second and third edition of the Keystone Training School in 2016 and 2017 on linked data tools, emphasizing practical ways to put linked data to use. She is a lecturer of Semantic Web (since 2011) and Database courses (since 2009) at the University of Modena and Reggio Emilia. She has authored approximately 40 publications in journals and proceedings of national and international conferences. Her research interests focus on data integration, metadata extraction, Semantic Web, NLP, linked data, open government data, and the smart city. She is leading a European Research Project on OpenData for Smart Cities called TRAFAIR "Understanding traffic flows to improve air quality" (www.trafair.eu). She co-founded the DataRiver S.r.l. n 2009, doing the Spin-Off designs and developing solutions for data integration using techniques from research in the field of the Semantic Web.

Dr. Nikos Bikakis is a postdoctoral researcher at the University of Ioannina, Greece. Before that, he was a postdoctoral researcher at ATHENA Research Center and Athens University of Economics & Business, as well as an adjunct lecturer at the University of West Attica, Greece. He received his Ph.D. in Computer Science from the National Technical University of Athens and his Diploma in Computer Engineering from the Technical University of Crete, Greece. Nikos has published more than 25 international research papers (book & encyclopedia chapters, journal articles, and conference papers). He has been awarded an honorary scholarship from the NTU Athens for his Ph.D. studies, and two Best Papers awards at international conferences. In 2018, his research in the field of Big Data visual analytics, was supported by anational/international research grant. He is co-organizing the annual international workshop on "Big Data Visual Exploration & Analytics" (BigVis 2020, 2019, and 2018). Additionally, he has served as a Guest Editor of the special issues "Big Data Visualization, Exploration, & Analytics" and "Interactive Big Data Visualization & Analytics" of the Big Data Research journal (Elsevier 2018 & 2020); and he was on the Guest Editorial Board for the special issue on "Visualization and Interaction for Ontologies & Linked Data," of the Journal of Web Semantics (Elsevier).His research interests include data exploration & visualization, data structures & algorithms, hard computational problems, personalized data management, heterogeneous databases, and Web of Data.

Federico Desimoni earned a Master's degree in Computer Engineering at the University of Modena and Reggio Emilia in 2019 with a thesis entitled "EmpiricalEvaluation of Linked Data Visualization Tool." He is currently a research fellow in the "Enzo Ferrari" Engineering Department at the University of Modena and Reggio Emilia, Italy. His research interests focus on Linked Data, Semantic Web, and Big Data Analysis.

Dr. George Papastefanatos has been a researcher in Information, Communication, and Knowledge Technologies for the Research and Innovation Center "Athena" at the Information Management Systems Institute (IMSI), since 2009. George obtained his Diploma on Electrical and Computer Engineering and his Ph.D. in Computer Science from the Department of Electrical and Computer Engineering of the National Technical University of Athens (NTUA) in 2000 and 2009, respectively. George has been involved as a senior researcher or scientific coordinator in the implementation of more than 15 EU and national research projects. He has also worked as an external IT expert in various private and public organizations such as National Statistical Service of Greece, ETVA VI.PE. S.A., Citibank, Greek Ministry of Education in the implementation of IT projects. From 2007 to 2011, he was an adjunct lecturer in University of Peloponnese and National School of Public Administration, and in 2018, he was a visiting lecturer in University of Aegean. George has more than 60 publications in international conferences and journals and has coauthored 3 chapters in books in the areas of big data management and analytics and, specifically, on issues related to semantic web data modelling, indexing and query optimization, data integration, data visualization, and visual analytics. Three of his articles have been selected as Best Papers in international conferences. He has supervised and contributed to the development of more than five prototype tools related to the management and visualization of LinkedData. In 2018, George was one of the receivers of a grant from the Hellenic Foundation for Research and Innovation for postdoc researchon the area of data visualization and visual analytics. He is co-organizing the International Workshop on Big Data Visual Exploration and Analytics, an annual event providing a forum for researchers and practitioners to discuss, exchange, and disseminate their work in the research areas of Data Management & Mining, Information Visualization, and Human-Computer Interaction. George has given several invited talks at conferences and events and served as a keynote speaker for the 8th International Workshop on Data Engineering meets the Semantic Web (DESWeb2017) in conjunction with the International Conference on Data Engineering (ICDE) 2017, giving a talk on "Visual Exploration in the Web of Data."

Product details

• Authors: Nikos Bikakis, Federico Desimoni, Federico et al Desimoni, George Papastefanatos, Laura Po
• Publisher: Springer, Berlin
• Original title: Linked Data Visualization
• Languages: English
• Product format: Hardback
• Released: 01.01.2020
• EAN: 9783031794919
• ISBN: 978-3-0-3179491-9
• No. of pages: 143
• Dimensions: 191 mm x 13 mm x 235 mm
• Weight: 508 g
• Illustrations: XIV, 143 p.
• Series: Synthesis Lectures on Data, Semantics, and Knowledge
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Miscellaneous