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Linked data visualization : = techni...
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Bikakis, Nikos
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 /
作者:
Po, Laura,
其他作者:
Bikakis, Nikos
面頁冊數:
1 PDF (xiii, 143 pages) :illustrations (some color). :
附註:
Part of: Synthesis digital library of engineering and computer science.
標題:
Linked data. -
電子資源:
https://ieeexplore.ieee.org/servlet/opac?bknumber=9048173
電子資源:
https://doi.org/10.2200/S00967ED1V01Y201911WBE019
ISBN:
9781681737263
Linked data visualization : = techniques, tools, and big data /
Po, Laura,
Linked data visualization :
techniques, tools, and big data /Laura Po, Nikos Bikakis, Federico Desimoni, George Papastefanatos. - 1 PDF (xiii, 143 pages) :illustrations (some color). - Synthesis lectures on data, semantics, and knowledge,#192160-472X ;. - Synthesis digital library of engineering and computer science..
Part of: Synthesis digital library of engineering and computer science.
Includes bibliographical references (pages 113-140).
1. Introduction -- 1.1. The power of visualization on linked data -- 1.2. The web of linked, open, and semantic data -- 1.3. Principles of linked data -- 1.4. The linked open data cloud -- 1.5. Web of data in numbers -- 1.6. The value and impact of linked and open data -- 1.7. Semantic web technologies -- 1.8. Conclusions
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
Compendex
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: 9781681737263
Standard No.: 10.2200/S00967ED1V01Y201911WBE019doiSubjects--Topical Terms:
1031097
Linked data.
Subjects--Index Terms:
linked dataIndex Terms--Genre/Form:
554714
Electronic books.
LC Class. No.: Z666.73.L56 / P655 2020eb
Dewey Class. No.: 025.024
Linked data visualization : = techniques, tools, and big data /
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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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