Linked Data: Evolving the Web into a Global Data Space

By Tom Heath, Christian Bizer. Linked Data, 2011

2,551 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/422c689b929e7ae7698ae8ed05bc16bbf637f3a9

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Citations in the corpus

Semantics : Science , Services and Agents on the World Wide Web (2014, background): “In the recent book ‘‘Linked Data: Evolving the Web into a Global Data Space’’ [65], Heath and Bizer make their only reference to blank nodes in the section entitled ‘‘RDF Features Best Avoided in the LinkedData Context’’, as follows:”
Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks (2016, background): “• WP (Heath and Bizer, 2011): This dataset consists of short snippets from Wikipedia.”
Adoption of the Linked Data Best Practices in Different Topical Domains (2014, background): “In order to enable Linked Data applications to discover datasets as well as to ease the integration of data from multiple sources, Linked Data publishers should comply with a set of best practices [4].”
Ontology Matching: State of the Art and Future Challenges (2013, background): “linked data [77] and the subsequent need for data interlinking.”
Linked data quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO (2017, background): “[27] introduce further criteria and metrics based on linked data guidelines for data publishers [24].”
Natural Language Questions for the Web of Data (2012, background): “DBpedia forms the nucleus of the Web of Linked Data (Heath and Bizer, 2011), which interconnects hundreds of RDF data sources with a total of 30 billion subject-property-object (SPO) triples.”
Ontology Matching (2007, methodology): “The web of data is made of data published following the following four principles (Berners-Lee 2009; Heath and Bizer 2011):”
Distributed learning: Developing a predictive model based on data from multiple hospitals without data leaving the hospital - A real life proof of concept. (2016, background): “Data stored in this way are said to be Linked Data [27] or Semantically Interoperable [28].”
Quality assessment for Linked Data: A Survey (2015, background): “– RDF graphs, which focus on entities assessment (where entities are described by a collection of RDF triples [28]).”