國立虎尾科技大學 |

Linked data visualization : = techniques, tools, and big data /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Linked data visualization :/ Laura Po, Nikos Bikakis, Federico Desimoni, George Papastefanatos.
其他題名:	techniques, tools, and big data /
其他題名:	Techniques, tools, and big data
作者:	Po, Laura,
其他作者:	Groth, Paul,
面頁冊數:	1 online resource (159 p.)
標題:	Semantic Web. -
電子資源:	https://portal.igpublish.com/iglibrary/search/MCPB0006529.html
ISBN:	1681737264

Linked data visualization : = techniques, tools, and big data /
Po, Laura,

Linked data visualization :techniques, tools, and big data /Techniques, tools, and big dataLaura Po, Nikos Bikakis, Federico Desimoni, George Papastefanatos. - 1 online resource (159 p.) - Synthesis lectures on data, semantics, and knowledge ;19. - Synthesis lectures on data, semantics, and knowledge ;#19..

Includes bibliographical references (pages 113-140).

Linked data visualization : techniques, tools, and big data -- Contents -- Preface -- Acknowledgments -- Chapter 1: Introduction -- Chapter 2: Principles of Data Visualization -- Chapter 3: Linked Data Visualization Tools -- Chapter 4: Visualization Use Cases -- Chapter 5: Empirical Evaluation of Linked Data Visualization Tools -- Chapter 6: Conclusions and Future Challenges -- Bibliography -- Authors' Biographies.

Access restricted to authorized users and institutions.

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.

Mode of access: World Wide Web.

ISBN: 1681737264Subjects--Topical Terms:

559260
Semantic Web.
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: QA76.9.I52

Dewey Class. No.: 001.4

Linked data visualization : = techniques, tools, and big data /
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520 3 $a 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.
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