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Linked Data
Linked Data allows evolving the web into a global data space by publishing structured data on the web using RDF and by linking data items across different data sources. It follows the Linked Data principles of using URIs to identify things and HTTP URIs to look up those names, providing useful RDF information when URIs are dereferenced, and including RDF links to discover related data. The amount of published Linked Data on the web has grown enormously since 2007. Large data sources like DBpedia extract structured data from Wikipedia and act as hubs by interlinking different data sets, enabling new applications and search over integrated data.
Linked Data
- 1. Linked Data - Evolvingthe Web into a Global Dataspace Anja Jentzsch - @anjeve Hasso Plattner Institute, Potsdam, Germany ! ! ! Open Data Lecture, HTW Berlin 2015/01/12
- 2. Architecture of theclassic Web B C HTMLHTML Web Browsers Search Engines hyper- links A HTML • Single global document space • Small set of simple standards • HTML as document format • HTTP URLs as globally unique IDs ! • Retrieval mechanism: Hyperlinks to connect everything
- 3. Web 2.0 APIsand Mashups No single global dataspace ! Shortcomings 1. APIs have proprietary interfaces 2. Mashups are based on a fixed set of data sources 3. No hyperlinks between data items within different APIs Web API A Mashup Web API B Web API C Web API D
- 4. Web APIs slicethe Web into Walled Gardens Image: Bob Jagensdorf, http://flickr.com/photos/darwinbell/, CC-BY
- 5. Extend the Webwith a single global dataspace 1. by using RDF to publish structured data on the Web 2. by setting links between data items within different data sources Linked Data B C RDF RDF Links A D E RDF Links RDF Links RDF Links RDF RDF RDF RDF RDF RDF RDF RDF RDF
- 6. Linked Data Principles Setof best practices for publishing structured data on the Web in accordance with the general architecture of the Web. 1. Use URIs as names for things. 2. Use HTTP URIs so that people can look up those names. 3. When someone looks up a URI, provide useful RDF information. 4. Include RDF statements that link to other URIs so that they can discover related things. Tim Berners-Lee, http://www.w3.org/DesignIssues/LinkedData.html, 2006
- 7. The RDF DataModel Anja Jentzsch dbpedia:Berlin foaf:name foaf:based_near foaf:Person rdf:type ns:anja
- 8. Data Items areidentified with HTTP URIs ns:anja = http://www.anjeve.de#anja dbpedia:Berlin = http://dbpedia.org/resource/Berlin foaf:name foaf:based_near foaf:Person rdf:type ns:anja dbpedia:Berlin Anja Jentzsch
- 9. Resolving URIs overthe Web dp:Cities_in_Germany 3.499.879 dp:population skos:subject dbpedia:Berlin foaf:name foaf:based_near foaf:Person rdf:type ns:anja Anja Jentzsch
- 10. Dereferencing URIs overthe Web dbpedia:Hamburg dbpedia:Muenchen skos:subject skos:subject dp:Cities_in_Germany 3.499.879 dp:population skos:subject dbpedia:Berlin foaf:name foaf:based_near foaf:Person rdf:type ns:anja Anja Jentzsch
- 11. RDF Representation Formats •RDF/XML <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:foaf="http://xmlns.com/foaf/0.1/"> <foaf:Person rdf:about="http://anjeve.de#anja"> <foaf:name>Anja Jentzsch</foaf:name> </foaf:Person> ! • RDF N-Triples <http://anjeve.de#anja> <http://www.w3.org/1999/02/22-rdf-syntax- ns#type> <http://xmlns.com/foaf/0.1/Person> . <http://anjeve.de#anja> <http://xmlns.com/foaf/0.1/name> „Anja Jentzsch“ .
- 12. RDF Representation Formats ! ! ! <http://anjeve.de#anja><http://www.w3.org/1999/02/22- rdf-syntax-ns#type> <http://xmlns.com/foaf/0.1/Person>. ! <Subject> <Predicate> <Object> . ! In the end it‘s all triples! foaf:Person rdf:type ns:anja
- 13. Properties of theWeb of Linked Data • Global, distributed dataspace build on a simple set of standards • RDF, URIs, HTTP • Entities are connected by links • creating a global data graph that spans data sets and • enables the discovery of new data sources • Provides for data-coexistence • Everyone can publish data to the Web of Linked Data • Everyone can express their personal view on things • Everybody can use the vocabularies/schemas that they like
- 14. W3C Linking OpenData Project • Grassroots community effort to • publish existing open license datasets as Linked Data on the Web • interlink things between different data sets
- 15. LOD Data Setson the Web: May 2007 • 12 data sets • 500+ million RDF triples • 120,000+ RDF links between data sets
- 16. LOD Data Setson the Web: November 2007 • 28 data sets
- 17. LOD Data Setson the Web: September 2008 • 45 data sets • 2+ billion RDF triples
- 18. LOD Data Setson the Web: July 2009 • 95 data sets • 6.5+ billion RDF triples
- 19. LOD Data Setson the Web: September 2010 • 203 data sets • Over 24,7 billion RDF triples • Over 436 million RDF links between data sets
- 20. LOD Data Setson the Web: September 2011 • 295 data sets • 31+ billion RDF triples • 504+ million RDF links between data sets http://lod-cloud.net
- 21. LOD Data Setson the Web:August 2014 http://lod-cloud.net • 1,019 data sets • 84+ billion RDF triples • 808+ million RDF links between data sets
- 22. LOD Data Setstatistics as of 08/2014 LOD Cloud Data Catalog on the Data Hub • http://datahub.io/group/lodcloud More statistics • http://lod-cloud.net/state/
- 23. Heterogeneity on theWeb of Data • The Web of Data is heterogeneous • Many different vocabularies are in use (469 as of January 2015) • Different data formats • Many different ways to represent the same information
- 24. DBpedia –The Hub on the Web of Data • DBpedia is a joint project with the following goals • extracting structured information from Wikipedia • publish this information under an open license on the Web • setting links to other data sources ! • Partners • Universität Mannheim (Germany) • Universität Leipzig (Germany) • OpenLink Software (UK)
- 25. Extracting structured datafrom Wikipedia
- 26. Extracting structured datafrom Wikipedia dbpedia:Berlin rdf:type dbpedia-owl:City , dbpedia-owl:PopulatedPlace , dbpedia-owl:Place ; rdfs:label "Berlin"@en , "Berlino"@it ; dbpedia-owl:population 3499879 ; wgs84:lat 52.500557 ; wgs84:long 13.398889 . ! dbpedia:SoundCloud dbpedia-owl:location dbpedia:Berlin . • access to DBpedia data: • dumps • SPARQL endpoint • Linked Data interface
- 27. The DBpedia DataSet • Information on more than 4.58 million “things” • 1,445,000 persons • 241,000 organisations • 735,000 places • 123,000 music albums • 87,000 movies • 251,000 species • overall more than 3 billion RDF triples • title and abstract in 125 different languages • 25,200,000 links to images • 29,800,000 links to external web pages • 50,000,000 links to other Linked Data sets
- 28. DBpedia Mappings • sinceMarch 2010 collaborative editing of • DBpedia ontology • mappings from Wikipedia infoboxes and tables to DBpedia ontology • curated in a public wiki with instant validation methods • http://mappings.dbpedia.org • multilingual mappings to the DBpedia ontology: • ar, be, bg, bn, ca, cs, cy, de, el, en, eo, es, et, eu, fr, ga, hi, hr, hu, id, it, ja, ko, nl, pl, pt, ru, sk, sl, sr, tr, ur, zh ! • allows for a significant increase of the extracted data’s quality • each domain has its experts
- 29. DBpedia Use Cases 1.Hub for the growing Web of Data 2. Improvement of Wikipedia search 3. Data source for applications and mashups 4. Text analysis and annotation
- 31. DBpedia Mobile • displaysWikipedia data on a map • aggregates different data sources
- 32. Faceted Wikipedia Search •faceted browsing and free text search
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- 35. Uptake in theGovernment Domain • The EU is pushing Linked Data (LOD2, LATC, EuroStat) • W3C eGovernment Interest Group
- 36. Uptake in theLibrary Community • Libraries publishing Linked Data • Library of Congress (subject headings) • German National Library (PND dataset and subject headings) • Swedish National Library (Libris - catalog) • Hungarian National Library (OPAC and Digital Library) • Europeana • W3C Library Linked Data Incubator Group • Goals: • Integrate library catalogs on global scale • Interconnect resources between repositories (by topic, by location, by historical period, by ...)
- 37. Uptake in LifeSciences • W3C Linking Open Drug Data Effort • Bio2RDF Project • Allen Brain Atlas ! ! ! ! ! ! • Goal: Smoothly integrate internal and external data in a pay-as-you-go-fashion.
- 38. Uptake in theMedia Industry • Publish data as Linked Data or RDFa • Goal: Drive traffic to websites via search engines
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- 40. Linked Data Browsers •Tabulator Browser (MIT, USA) • Marbles (MES / Uni Mannheim, DE) • OpenLink RDF Browser (OpenLink, UK) • Zitgist RDF Browser (Zitgist, USA) • Humboldt (HP Labs, UK) • Disco Hyperdata Browser (Uni Mannheim, DE) • Fenfire (DERI, Irland)
- 42. Web of DataSearch Engines • Sig.ma (DERI, Ireland) • Falcons (IWS, China) • Swoogle (UMBC, USA) • VisiNav (DERI, Ireland) • Watson (Open University, UK)
- 44. 44 Finding Linked Datasets • Search engines • find data sets based on keywords ! • Data catalogs / directories • explore data sets and faceted search ! • Data Marketplaces • explore and consume data sets
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- 46. Is your data5 star? Tim Berners-Lee, http://www.w3.org/DesignIssues/LinkedData.html, 2010 Make your data available on the Web (in whatever format) under an open license. Make it available as structured data (e.g., Excel instead of image scan of a table) so that it can be reused. Use non-proprietary, open formats (e.g., CSV instead of Excel). ! Use URIs to identify things, so that people can point at your stuff and serve RDF from it. Link your data to other data to provide context. ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★
- 47. Economic Opportunities • Hugereservoir of free content which can be used to provide background facts about • places, • people, • topics • … Background Facts
- 48. schema.org • jointly proposedvocabularies for embedding data into HTML pages (Microdata) • available since June 2011
- 49. Options for SearchCompanies • New vertical search engines • Sig.ma, FalconS, … • Google Knowledge Graph • 1.6 billion facts (2014) • Yahoo • Improving text search with background knowledge
- 50. Lower Data IntegrationCosts Overall data integration effort is split between: ! • Data Publisher – publishes data as RDF – sets identity links – reuses terms or publishes mappings • Third Parties – set identity links pointing at your data – publish mappings to the Web • Data Consumer – has to do the rest – using record linkage and schema matching techniques
- 51. Conclusion • The Webof Data is growing fast • Linked Data provides a standardized data access interface • Allows for easy data integration, enhancement and browsing • Web search is evolving into query answering • Search engines will increasingly rely on structured data from the Web • Next step: Linked Data within enterprises • Alternative to data warehouses and EAI middleware • Advantages: schema-less data model, pay-as-you go data integration
- 52. Thanks! References: • Tom Heath,Christian Bizer: Linked Data: Evolving the Web into a Global Data Space http://linkeddatabook.com/ • Linking Open Data Project Wiki http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData Email: anja@anjeve.de Twitter: @anjeve