Ontology Matching and the Semantic Web

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1 Ontology Matching and the Semantic Web Heiko Paulheim TU Darmstadt, Knowledge Engineering Group / SAP Research Darmstadt WeRC Interdisciplinary Talk Series April 26th, 2011 April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 1

2 Outline The Semantic Web in a Nutshell Vision The Role of Ontologies RDF, OWL, Linked Open Data, RDFa, the State of the Art Ontology Matching Motivation Approaches and Tools Current Research Directions Conclusion April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 2

3 The Vision by Tim Berners-Lee et al. (2001) The Web is the killer app of the Internet. The Semantic Web is another killer app of that magnitude. Berners-Lee, Hendler, and Lassila (2001) April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 3

4 The Classic Web What a human sees: <html> dr. Mark Smith physician Main St. 14 Smalltown Mon-Fri 9-11 am Wed 3-6 pm </html> What a machine sees: Dr. Mark Smith Physician Main St. 14 Smalltown Mon-Fri 9-11 am Wed 3-6 pm Print in bold: hmf298hmmhudsa Print in italics: mj2i9ji0 Print normal: fdsah 02hfadsh0um2m0adsmf0ihm asdfjköfdsa298ndsfmij32mio lk2mjpoimjiofdpmsajiomjm April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 4

5 Querying the Web Keyword search (e.g., Google): Mark Smith Physician in Smalltown Doctor in Smalltown Physician in Smalltown who has opening hours on Wednesday afternoon Somebody in Smalltown who can fix a broken leg <html> dr. Mark Smith physician Main St. 14 Smalltown Mon-Fri 9-11 am Wed 3-6 pm </html> the classic web is inflexible for searching intelligent agents could help, but cannot access it April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 5

6 Machines Need a Different Data Representation <html> dr. Mark Smith physician Main St. 14 Smalltown Mon-Fri 9-11 am Wed 3-6 pm </html> Representation in machine-processable form PREFIX ms:person a dbpedia:physician. ms:person address ms:addr. ms:person name Mark Smith ms:addr street Main St. 14 ms:addr city Smalltown April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 6

7 Triples (Sentences) and Graphs PREFIX ms:person a dbpedia:physician. ms:person address ms:addr. ms:person name Mark Smith ms:addr street Main St. 14 ms:addr city Smalltown April 5,

8 Is that Enough? SPARQL Queries: SELECT?p WHERE {?p a Physician,?p address?a?a city Smalltown } SELECT?p WHERE {?p a MedicalDoctor, } SELECT?p WHERE {?p a Person,?p canfix?bl,?bl a BrokenLeg } PREFIX ms:person a dbpedia:physician. ms:person address ms:addr. ms:person name Mark Smith ms:addr street Main St. 14 ms:addr city Smalltown April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 8

9 So What is Missing? Physicians are doctors who can fix injuries such as broken legs I need someone in Smalltown who can fix a broken leg Dr. Mark Smith Physician Main St. 14 Smalltown Mon-Fri 9-11 am Wed 3-6 pm April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 9

10 Ontologies in the Semantic Web Ontologies contain formalized knowledge about a domain. April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 10

11 Let s Try Again SPARQL Queries: SELECT?name WHERE {?p a Physician,?p address?a?a city Smalltown } SELECT?name WHERE {?p a MedicalDoctor, } SELECT?name WHERE {?p a Person,?p canfix?bl,?bl a BrokenLeg } PREFIX ms:person a dbpedia:physician. ms:person address ms:addr. ms:person name Mark Smith ms:addr street Main St. 14 ms:addr city Smalltown + April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 11

12 The Semantic Web Subject of ongoing research Core Semantic Web Technology Foundations Berners-Lee (2009) April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 12

State of the Art Cyganiak and Jentzsch (2010), http://lod-cloud.

13 State of the Art Cyganiak and Jentzsch (2010), April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 13

14 What Data is Out There? ~300 interlinked data sets ~35 billion RDF triples Publications Government Data Geo Data Life Sciences General Data, e.g. DBPedia April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 14

15 State of the Art: Linked Data The four rules for Linked Data by Tim Berners-Lee (2006): 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 information, using standards (RDF, SPARQL) 4. Include links to other URIs, to that they can discover more things PREFIX ms: ms:person a dbpedia:physician. ms:person address ms:addr. ms:person name Mark Smith ms:addr street Main St. 14 ms:addr city Smalltown April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 15

16 So, Are There Going to Be Two Webs? <html> dr. Mark Smith physician Main St. 14 Smalltown Mon-Fri 9-11 am Wed 3-6 pm </html> HTML (for humans) RDF (for machines) HTML+RDFa (for everybody) PREFIX <html> Dr. Mark Smith physician main St. 14 smalltown </html> ms:person a dbpedia:physician. ms:person address ms:addr. ms:addr addr:street Main St. 14 ms:addr addr:city Smalltown April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 16

RDFa is Slowly Growing Mainstream Major websites are currently adopting RDFa, e.g. BestBuy O Reilly BBC Music and Google uses RDFa for rendering of search results: http://rdfa.

17 RDFa is Slowly Growing Mainstream Major websites are currently adopting RDFa, e.g. BestBuy O Reilly BBC Music and Google uses RDFa for rendering of search results: April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 17

18 First Half Wrap-Up Semantic web provides information for humans and machines Ontologies give meaning to data RDFa provides fusion into one web April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 18

19 Deriving Information from Various Data Sets Find a researcher based in Hesse who has published about ontology matching To resolve such a query, we have to use different sources, e.g.: April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 19

20 Deriving Information from Various Data Sets April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 20

21 Ontologies in the Semantic Web Recap: Ontologies are the languages of the semantic web Many of such languages are used (10,000 already as of 2007) Linked Open Data is not restricted to any ontologies: Data publishers are not constrained in choice of vocabularies with which to represent data. Thus, the Semantic Web is like the WWW it speaks many languages (and even worse, since there is no de facto standard) Bizer et al. (2009) April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 21

22 Ontology Mappings Dictionaries for Ontologies Ontologies Instances April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 22

23 Ontology Matching Ontology Matching = finding ontology mappings Fully or semi automatic April 5,

24 Approaches to Ontology Matching Euzenat and Shvaiko (2007) April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 24

25 State of the Art: Selected Tools AgrMaker (Cruz et al., 2010) ASMOV (Jean-Mary et al., 2010) Eff2Match (Khong Chua and Kim, 2010) Falcon (Hu et al., 2010) MapPSO (Bock, 2010) RiMoM (Wang et al., 2010) Performance of those tools: 50-80% F-Measure Strongly depending on the type of task April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 25

26 Current Trends in Ontology Matching Discovery and use of background knowledge Mapping validation Expressing and finding complex mappings Scalability and performance Matcher selection, combination, and parametrization Interactive user feedback and collaborative matching April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 26

27 Wrap-Up The semantic web provides information accessible for humans and machines Ontologies are the languages of the semantic web Ontology mappings are links between ontologies A useful extension to the Semantic Web: Linked Open Data links instances Ontology mappings link ontologies Ontology matching: finding mappings (semi) automatically April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 27

28 Further Reading Hitzler et al. (2008): Semantic Web. Grundlagen. Staab and Studer (eds.) (2009): Handbook on Ontologies. Bizer et al (2009): Linked Data the Story so Far. Euzenat and Shvaiko (2007) Ontology Matching. Shvaiko and Euzenat (2008): Ten Challenges for Ontology Matching. April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 28

29 Ontology Matching and the Semantic Web Questions? April 26th, 2011 Department of Computer Science Knowledge Engineering Group Heiko Paulheim 29

The Data Web and Linked Data.

Mustafa Jarrar Lecture Notes, Knowledge Engineering (SCOM7348) University of Birzeit 1 st Semester, 2011 Knowledge Engineering (SCOM7348) The Data Web and Linked Data. Dr. Mustafa Jarrar University of