Linked Data - Bizer, Christian

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Résumé :
The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study. Table of Contents: List of Figures / Introduction / Principles of Linked Data / The Web of Data / Linked Data Design Considerations / Recipes for Publishing Linked Data / Consuming Linked Data / Summary and Outlook

Biographie:
Dr. Tom Heath is lead researcher at Talis, a Birmingham, UK-based software company and global leader in the research, development and commercial exploitation of Linked Data and Semantic Web technologies. At Talis, he is responsible for leading internal research exploring how Linked Data affects the sharing and reuse of data, the value and insights that can be derived from this data, and the implications of these changes for human-computer interaction. Tom has a first degree in psychology from the University of Liverpool and a PhD in Computer Science from The Open University's Knowledge Media Institute. His doctoral research examined how a richer understanding of trust decisions in word-of-mouth recommendation can be combined with Semantic Web technologies and social networks to improve the personal relevance of information-seeking processes on the Web. Tom has been active in the Linked Data community since its inception in early 2007, creating the Linked Data reviewing and rating site Revyu.com that went on to win first prize in the 2007 International Semantic Web Challenge. In addition to co-founding the highly successful workshop series Linked Data on the Web, held at the International World-wide Web Conference since 2008, he has served as chair of the Semantic Web In-use track at both the International and European Semantic Web Conferences, and he co-authored the seminal article Linked Data - The Story So Far with Christian Bizer and Tim Berners-Lee. In 2009, Tom was named PhD of the Year 2008/9 by STI International, and in 2011 one of AI's 10 to Watch by IEEE Intelligent Systems. Prof. Dr. Christian Bizer is the head of the Web-based Systems Group at Freie Universit?t Berlin, Germany. He explores technical and economic questions concerning the development of global, decentralized information environments. The current focuses of his research are data integration, identity resolution, and information quality assessment in the context of the Web of Data. Theresults of his work include the Named Graphs data model which was adopted into the W3C SPARQL recommendation...

Sommaire:
List of Figures.- Introduction.- Principles of Linked Data.- The Web of Data.- Linked Data Design Considerations.- Recipes for Publishing Linked Data.- Consuming Linked Data.- Summary and Outlook.