The document discusses using Watson, a gateway to the Semantic Web, to both develop applications that exploit online semantic resources and to better understand the Semantic Web. It describes how Watson allows applications to dynamically retrieve and combine relevant ontologies and data. It also explains how Watson has been used as a research platform to characterize ontologies in its collection, understand relations between ontologies, and measure agreement between statements and ontologies.

1. Exploiter le Web Sémantique, le comprendre et ycontribuer(danscetordre) Mathieu d’Aquin KMi, The Open University – m.daquin@open.ac.uk Le reste des diapossontprincipalement en anglais… The other slides are mostly in English

2. Outline of the talk 1. 2. Exploiter le Web Sémantique, le comprendre et ycontribuer 4. 3.

3. Outline of the talk ? Exploiter le Web Sémantique, le comprendre et ycontribuer

4. The Semantic Web (in theory) A large scale, heterogenous collection of formal, machine processable, ontology-based statements (semantic metadata) about web resources and other entities in the world, expressed in a standard syntax <rdf:RDF> <owl:Ontologyrdf:about=""> <owl:importsrdf:resource="http://usefulinc.com/ns/doap#"/> </owl:Ontology> <j.1:Organization rdf:ID="KMi"> <rdfs:commentrdf:datatype="http://www.w3.org/2001/XMLSchema#string" >The Knoledge Media Institute of the Open University, Milton Keynes UK</rdfs:comment> </j.1:Organization> <j.1:Document rdf:ID="KMiWebSite"> … <rdf:RDF> <channel rdf:about=“http://watson.kmi.open.ac.uk/blog”> <title>Elementaries - The Watson Blog</title> <link>http://watson.kmi.open.ac.uk:8080/blog/</link> <description> "Oh dear! Where the Semantic Web is going to go now?" -- imaginary user 23 </description> <language>en</language> <copyright>Watson team</copyright> <lastBuildDate>Thu, 01 Mar 2007 13:49:52 GMT</lastBuildDate> <generator>Pebble (http://pebble.sourceforge.net)</generator> <docs>http://backend.userland.com/rss</docs> …

5. Galen NCI … Music DC WORDNET RSS TAP FOAF … … … … Metadata <rdf:RDF> <channel rdf:about=“http://watson.kmi.open.ac.uk/blog”> <title>Elementaries - The Watson Blog</title> <link>http://watson.kmi.open.ac.uk:8080/blog/</link> <description> "Oh dear! Where the Semantic Web is going to go now?" -- imaginary user 23 </description> <language>en</language> <copyright>Watson team</copyright> <lastBuildDate>Thu, 01 Mar 2007 13:49:52 GMT</lastBuildDate> <generator>Pebble (http://pebble.sourceforge.net)</generator> <docs>http://backend.userland.com/rss</docs> … <rdf:RDF> <foaf:Imagerdf:about='http://static.flickr.com/132/400582453_e1e1f8602c.jpg'> <dc:title>Zen wisteria</dc:title> <dc:description></dc:description> <foaf:pagerdf:resource='http://www.flickr.com/photos/xcv/400582453/'/> <foaf:topicrdf:resource='http://www.flickr.com/photos/tags/vittelgarden/'/> <foaf:topicrdf:resource='http://www.flickr.com/photos/tags/wisteria/'/> <dc:creator> <foaf:Person><foaf:name>Mathieu d'Aquin</foaf:name> … <rdf:RDF> <owl:Ontologyrdf:about=""> <owl:importsrdf:resource="http://usefulinc.com/ns/doap#"/> </owl:Ontology> <j.1:Organization rdf:ID="KMi"> <rdfs:commentrdf:datatype="http://www.w3.org/2001/XMLSchema#string" >The Knoledge Media Institute of the Open University, Milton Keynes UK</rdfs:comment> </j.1:Organization> <j.1:Document rdf:ID="KMiWebSite"> … UoD

6. <rdf:RDF> <owl:Ontologyrdf:about=""> <owl:importsrdf:resource="http://usefulinc.com/ns/doap#"/> </owl:Ontology> <j.1:Organization rdf:ID="KMi"> <rdfs:commentrdf:datatype="http://www.w3.org/2001/XMLSchema#string" >The Knoledge Media Institute of the Open University, Milton Keynes UK</rdfs:comment> </j.1:Organization> <j.1:Document rdf:ID="KMiWebSite"> … <rdf:RDF> <foaf:Imagerdf:about='http://static.flickr.com/132/400582453_e1e1f8602c.jpg'> <dc:title>Zen wisteria</dc:title> <dc:description></dc:description> <foaf:pagerdf:resource='http://www.flickr.com/photos/xcv/400582453/'/> <foaf:topicrdf:resource='http://www.flickr.com/photos/tags/vittelgarden/'/> <foaf:topicrdf:resource='http://www.flickr.com/photos/tags/wisteria/'/> <dc:creator> <foaf:Person><foaf:name>Mathieu d'Aquin</foaf:name> … Ontology alignment Data integration Data analysis Reasoning Etc. Smart Application

7. Many research and development efforts in Supporting the design of ontologies (methodologies, toolkits, editors, etc.) Supporting the annotation Web resources (natural language processing, information extraction, etc.) Supporting the publication of semantic data and information online (linking open data, `semantification’ of legacy information systems) … Resulting in an explosion of the amount of machine processable knowledge online. Therefore…

8. OK, nice… but what’s the reality? 2007 2008 2009

9. Slide 9 And for ontologies?

10. Slide 10 And for ontologies?

11. Millions of Semantic Web documents (data), containing billions of RDF triples Thousands of ontologies online in OWL and RDFs, covering many different domains (will talk about that later) But, distributed and heterogeneous in representation, meaning, quality… So, what do we really do with it? So, the Semantic Web in reality?

12. Outline of the talk ? Exploiter le Web Sémantique, le comprendre et ycontribuer

14. Dynamically retrieving the relevant semantic resources

16. Watson: a Gateway to the Semantic Web

17. Architecture

18. Interface http://watson.kmi.open.ac.uk

19. But the important part is: the APIs Provide Semantic Web application developers with the ability to efficiently: Locate (find) Semantic Web documents online using advanced search functions Explore the documents, automatically extracted metadata and content Query the documents, to exploit online knowledge in an homogeneous way In a set of lightweight APIs, and without having to download the data or use any other dedicated infrastructure.

20. Some Applications We Developed Semantic Relation Discovery: Scarlet Ontology Reuse: The Watson Plugin Question Answering: PowerAqua Folksonomy Enrichment And also: Word sense disambiguation Query Expansion Synonym Discovery Web Service Annotation… Semantic Browsing: PowerMagpie

21. Chose an entity to search Integrate statements Into the edited ontology Get entities from online ontologies Example: The Watson Plugin

22. Example: Scarlet SeaFood Meat wine.owl AcademicStaff Semantic Web Semantic Web Researcher ka2.rdf Meat SeaFood Ham pizza-to-go NALT AcademicStaff Researcher Ham SeaFood ISWC SWRC NALT Agrovoc

23. Example: Scarlet http://scarlet.open.ac.uk/

24. Example: Wahoo http://watson.kmi.open.ac.uk/wahoo

25. Example: PowerAqua Natural language question Answers from online semantic data

26. Example: FLOR Can the Semantic Web provide the structure needed to improve search and navigation of tagged spaces?

27. Dog Bird Land scape Dog Bird Cat Land scape Bird Dog Tiger Tiger Bird Dog Land scape Bird Bird Bird Tiger Tiger Search in Tag Spaces Let’s find photos of “animals which live in the water” Query: Animal Water 5/24 ≈ 21% relevant

28. Bring in the SW… Animal Water Animal livesIn Body of Water Mammal Fish <Animal livesIn Water> livesIn SaltwaterFish FreshwaterFish Sea <Dolphin>or<Seal> or <“Sea Elephant”>or <Whale> livesIn Marine Mammal Ocean Dolphin Seal Whale Sea Elephant

29. Results dolphin seal whale sea elephant 18/24 ≈ 75% relevant

30. SWEET: Semantic Annotation of REST services

31. These are only a few of the applications developed in KMi (i.e., us, the people who are doing Watson) Many other people are developing such applications (and we don’t necessarily know all of them) Many other tools exists that help building applications (triple stores, query engines, other Semantic Web search engines)… But what does that tell us about the Semantic Web? And so?

32. Outline of the talk Exploiter le Web Sémantique, le comprendre et ycontribuer ?

33. Watson collects a lot of ontologies and Semantic Web documents that are created by different people for different purposes In addition to being a gateway for the development of applications exploiting this knowledge, it can be used to better understand how knowledge is published online, how the Semantic Web looks like, and how it evolves Watson as a Research Platform

34. Characterizing and subset of the Watson Collection (2007) Underlying description logic Number of entities Domain covered

35. Ontologies are naturally related with each other, some are equivalent to others, some are versions, some are similar, some are incompatible to each other These relations generally stay implicit Understanding relations between ontologies online Better understanding these relations is useful to support the use of the Semantic Web

36. DOOR: An Ontology of Ontology Relations

37. Ontologies evolve on the Web, there are many different versions of the same ontology are available This is rarely made explicit through the appropriate metadata for ontologies (e.g., owl:preVersion) But version info is often encoded in the URIs of ontologies, e.g., http://loki.cae.drexel.edu/wbs/ontology/2003/10/iso-metadata http://loki.cae.drexel.edu/wbs/ontology/2004/01/iso-metadata Extracting this information can help in studying the evolution of ontologies on the Semantic Web, i.e., the Semantic Web dynamics Example Relation: Different Versions

38. We developed simple method based on a few rules recognizing specific patterns in the differences between URIs of ontologies (dates, timestamps, etc.) and ran it on a set of 6,898 ontologies from Watson. We found 155,501 (directed) versioning relations between these ontologies, which represent 1,365 evolving ontologies A manual evaluation indicates that more than 50% of these are correct Next step: improve the method and study evolution patterns on the Semantic Web Example Relation: Different Versions – Initial Experiment

39. Ontologies are knowledge artifacts, they express opinions and beliefs and contradict each others Assessing (dis)agreement in ontologies is very useful to understand how to combine knowledge from different sources A possible approach would be to check whether inconsistencies and incoherencies appear while combining the ontologies. However we believe that: There are different levels of agreement/disagreement Covering different domains is not agreeing It is possible to agree and disagree at the same time Based on these requirements we define a set of measures for assessing (dis)agreement between statements and ontologies. Example Relations: Agreement and Disagreement

40. Agreement(st, O)  [0..1] and Disagreement(st, O)  [0..1] where stis a statement <subject, predicate, object> and O is an ontology Based on extracting the part of the ontology that express a relation between subject and object (Dis)agreement between ontologies: Global (dis)agreement in a repository Consensus: Controversy: Example Relations: Agreement and Disagreement - Measures

41. Experiment: assessing statements related to the class Seafood in Watson: a: global agreement, d: global disagreement, cs: consensus, ct: controversy More experiments on the Way! Example Relations: Agreement and Disagreement – Application?

42. Using 21 ontologies containing a concept SeaFood Camp 1: seaFooddisjointWith Meat Camp 2: SeaFoodsubClassOf Meat Disagreement Agreement

43. Outline of the talk Exploiter le Web Sémantique, le comprendre et ycontribuer ?

44. Slide 43 From a Semantic Web search engine…

45. Slide 44 Comments and Reviews Ontology Metadata Alignments Versions of … to Ontology Repositories? Ontologies

46. Cupboard.open.ac.uk

47. Metadata Summary Reviews

48. I hope I convinced you that Using the Semantic Web Understanding the Semantic Web  Contributing to the Semantic Web Through Watson, Cupboard and our applications, our aim is to build an open and efficient platform making the Semantic Web a `playground for research and development’ There is still a lot to do, and everybody is welcome to comment, help, contribute… Final message

49. Thank You! Mathieu d’Aquin (m.daquin@open.ac.uk, http://people.kmi.open.ac.uk/mathieu) With contributions from many people in KMi (http://kmi.open.ac.uk) and the NeOn project (http://neon-project.org) /* I would normally include a bibliography slide at the end, but all the relevant papers can be found on these 3 websites */