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Linked Data Visualization: Techniques, Tools, and Big Data

Synthesis Lectures on the Semantic Web: Theory and Technology

Laura Po​‌
University of Modena and Reggio Emilia, Italy
Nikos Bikakis​‌
University of Ioannina, Greece
Federico Desimoni​‌
University of Modena and Reggio Emilia, Italy
George Papastefanatos​‌
ATHENA Research Center, Greece


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 adopted as the established practice 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 topics, 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 core concepts related to data visualization and LD technologies, techniques employed for data visualization based on the characteristics of data, techniques for Big Data visualization, 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 as a primer for all those interested in LD and data visualization.

Table 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

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Laura Po
Nikos Bikakis
Federico Desimoni
George Papastefanatos
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