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In computing, linked data is structured data which is associated with ("linked" to) other data. Interlinking makes the data more useful through semantic queries. Tim Berners-Lee, director of the World Wide Web Consortium (W3C), coined the term in a 2006 design note about the Semantic Web project. Part of the vision of linked data is for the Internet to…
The analysis highlights Art, Linked open data and Components as prominent areas in the source structure around Linked data. 1 topic appears in more than one source area, which can help identify connections that are less obvious in a linear reading.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Linked data shows recurring relationship patterns in the source. For example, Linked data → AKN4EU, DaPaaS, Data, Data-and-Platform-as-a-Service, EU Open Data Portal, European Union, LATC, Linked Open Data, LOD2, PlanetData, There, These Another extracted example is Linked data → HTTP URI-based, HTTP URIs, In, RDF, SPARQL, Tim Berners-Lee, Uniform Resource Identifiers, URIs, Useful, Web, When. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
data linked open rdf http web datasets uris tim berners-lee links project w3c structured using semantic also triples name available
TTTA extracted 62 structured relationships around Linked data. Examples in this analysis include HTTP → instance of → Part of the vision of linked data is for the Internet to become a global database.Linked data builds upon standard Web technologies and RDF → instance of → Useful information about what a name identifies should be provided through open standards. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| HTTP | instance of | Part of the vision of linked data is for the Internet to become a global database.Linked data builds upon standard Web technologies | 0.80 | text |
| RDF | instance of | Part of the vision of linked data is for the Internet to become a global database.Linked data builds upon standard Web technologies | 0.80 | text |
| URIs | instance of | Part of the vision of linked data is for the Internet to become a global database.Linked data builds upon standard Web technologies | 0.80 | text |
| but rather than using them to serve web pages | instance of | Part of the vision of linked data is for the Internet to become a global database.Linked data builds upon standard Web technologies | 0.80 | text |
| hyperlinks only for human readers | instance of | Part of the vision of linked data is for the Internet to become a global database.Linked data builds upon standard Web technologies | 0.80 | text |
| it extends them to share information in a way that can be read automatically by computers | instance of | Part of the vision of linked data is for the Internet to become a global database.Linked data builds upon standard Web technologies | 0.80 | text |
| RDF | instance of | Useful information about what a name identifies should be provided through open standards | 0.80 | text |
| SPARQL | instance of | Useful information about what a name identifies should be provided through open standards | 0.80 | text |
| etc.When publishing data on the Web | instance of | Useful information about what a name identifies should be provided through open standards | 0.80 | text |
| other things should be referred to using their HTTP URI-based names.Tim Berners-Lee later restated these principles at a 2009 TED conference | instance of | Useful information about what a name identifies should be provided through open standards | 0.80 | text |
| again paraphrased along the following lines | instance of | Useful information about what a name identifies should be provided through open standards | 0.80 | text |
| RDFa | instance of | URIsHTTPStructured data using controlled vocabulary terms and dataset definitions expressed in Resource Description Framework serialization formats | 0.80 | text |
The concept neighborhoods around Linked data bring nearby vocabulary together. In this analysis, examples include Linked, Open and Berners-lee. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Linked data, one of the stronger structural bridges in this analysis connects Linked data with Linked open data. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Linked data to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Art, Linked open data & Components, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Linked data · EN edition · Analysis: TopicsToTalkAbout