1. The Web of Linked Data Information Universe Seongmin Lim hovern@snu.ac.kr Dept. of Industrial Engineering Seoul National University

2. contents  Foundations of Dataspaces and Linked Data -Where do they overlap?  The Web of Linked Data -What data is out there?  Linked Data Applications -What is being done with the data?  Remarks on -Identity -Self-descriptive Data -Pay-as-you-go Integration 2

3. From data integration systems to dataspace  In order to cope with growing number of data sources  Properties of dataspaces -may contain any kind of data (structured, semi-structured, unstructured) -require no upfront investment into a global schema -provide for data-coexistence -give best-effort answers to queries -rely on pay-as-you-go data integration 3

4. Linked data principles  For publishing structured data on the general Web  Tim Berners-Lee 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. 4

5. From classic web to web 2.0 Single global information space No single global dataspace 1.Small set of simple standards1. APIs have proprietary interfaces 2.Hyperlinks to connect everything2. Mashups from a fixed data sources 3. No hyperlinks within different APIs 5

6. Web APIs slice the Web into Walled Gardens

7. Can’t we just publish data as files?  pdf -Easy to read and publish  Excel -Allows further processing and analysis  csv -Processing without need for proprietary tools But… -Structure of data not explained -No connection between different data sets, silos -Static and fixed – can’t retrieve just slices relevant to problem 7

8. Linked data  Extend the Web with a single global dataspace -By using RDF to publish structured data on the Web -By setting links between data items within different data sources 8

9. What is RDF?  Resource Description Framework  RDF is the data format for linked data  It’s about writing down relations between things  What is RDF for? -For everyone to do same for data -To make the Web into a database 9

10. The essence of RDF: the ‘triple’  Typical database table 10 things propertiess

11. Relations between ‘things’ 11

12. Using the Web’s infrastructure  Entities are identified with HTTP URIs -Specifically http:// 12

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14. contents  Foundations of Dataspaces and Linked Data -Where do they overlap?  The Web of Linked Data -What data is out there?  Linked Data Applications -What is being done with the data?  Remarks on -Identity -Self-descriptive Data -Pay-as-you-go Integration 14

15. Properties of the Web of linked data  Global, distributed dataspace built on a simple set of standards -RDF, URIs, HTTP  Entities are connected by links -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 schemata that they like for this 15

16. W3C linking open data project  Publish existing open license datasets as linked data  Interlink things between different data sources  2007 16

17. LOD datasets on the Web: July 2009 17

18. DBpedia  community effort to extract structured information from Wikipedia.  provides data about 3.4 million things -312,000 persons -140,000 organizations -413,000 places -94,000 music albums -49,000 films -146,000 species -…  provides identifiers for many common things -http://dbpedia.org/resource/Calgary  overlaps with many other data sources on the Web 18

19. Uptakes in many areas  Uptake in life sciences -W3C linking open drug data effort -Bio2RDF project -Allen Brain Atlas  Governments, libraries, media industry, …… 19

20. The structural continuum  The Web of linked data is interwoven with the classic Web. -Unstructured data: HTML -Semi-structured data: RDFa embed into HTML -Structured data: RDF/XML  Services using named entity recognition to annotate texts with Linked Data URIs -Open Calais (Thomsons Reuters) for news -Zemanta (startup) for blog posts 20

21. contents  Foundations of Dataspaces and Linked Data -Where do they overlap?  The Web of Linked Data -What data is out there?  Linked Data Applications -What is being done with the data?  Remarks on -Identity -Self-descriptive Data -Pay-as-you-go Integration 21

22. Linked data browsers  Provide for navigating between data sources in order to explore the dataspace. -Tabulator Browser (MIT, USA) -Marbles (FU Berlin, DE) -OpenLink RDF Browser (OpenLink, UK) -Zitgist RDF Browser (Zitgist, USA) -Disco Hyperdata Browser (FU Berlin, DE) -Fenfire (DERI, Irland) 22

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24. Mashups(DBpedia mobile) 24

25. Web of data search engines  Crawl the dataspace and provide best-effort query answers over crawled data. -Falcons (IWS, China) -Sig.ma (DERI, Ireland) -Swoogle (UMBC, USA) -VisiNav (DERI, Ireland) -Watson (Open University, UK) 25

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27. What are the big players doing?  Yahoo! and Google have started to crawl Linked Data in its RDFa serialization as well as Microformats.  Yahoo! -provides access to crawled data through the Yahoo BOSS API -is using the data within Yahoo Search Monkey to make search results more useful and visually appealing.  Google -uses crawled RDF data for its Social Graph API -uses crawled data to enhance search results snippets for reviews and people. 27

28. Yahoo! Search monkey 28

29. contents  Foundations of Dataspaces and Linked Data -Where do they overlap?  The Web of Linked Data -What data is out there?  Linked Data Applications -What is being done with the data?  Remarks on -Identity -Self-descriptive Data -Pay-as-you-go Integration 29

30. Identity  Real world objects are identified with multiple URIs -Coupling of identification and retrieval -Data-coexistence: everybody can say everything about anything 30

31. Enable Clients to retrieve the Schema  Clients can resolve the URIs that identify vocabulary terms in order to get their RDFS or OWL definitions. 31

32. Reuse Terms from Common Vocabularies  Common Vocabularies -Friend-of-a-Friend for describing people and their social network -SIOC for describing forums and blogs -SKOS for representing topic taxonomies -Organization Ontology for describing the structure of organizations -GoodRelations for describing products and business entities -Music Ontology for describing artists, albums, and performances -Review Vocabulary provides terms for representing reviews  Common sources of identifiers (URIs) for real world objects -LinkedGeoData and Geonames: Locations -GeneID and UniProt: Life science identifiers -Dbpedia: Wide range of things 32

33. Somebody Pays-As-You-Go  The overall data integration effort is split between the data publisher, the data consumer and third parties.  Data Publisher -publishes data as RDF -publishes data in a self-descriptive fashion -sets links and publishes mappings  Third Parties -set links pointing at your data -publish mappings to the Web  Data Consumer -has to do the rest 33

34. Summary  Linked Data moves the dataspace vision to a global scale and adds the social/community aspect to it.  The Web of Linked Data is growing rapidly -active deployment communities in different domains -might have exceeded the critical mass  Great playground for experimentation -dataspace profiling -probabilistic and approximate schema mapping -data fusion, data quality, and trust -What will the user interfaces look like? -Will search engines turn into answer engines? 34

35. End of Document Seongmin Lim hovern@snu.ac.kr Dept. of Industrial Engineering Seoul National University