DE Conferentie 2007 Jack van Ossenbruggen


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DE Conferentie 2007 Jack van Ossenbruggen

  1. 1. Steps towards a Culture Web Tumbling Walls & Building Bridges
  2. 2. Interoperability: tearing downthe walls between collections• Musea have increasingly nice websites• But: most of them are driven by stand-alone collection databases• Data is isolated, both syntactically and semantically• If users can do cross-collection search, the individual collections become more valuable! 2
  3. 3. The Web:“open” documents and links URL Web link URL 3
  4. 4. The Semantic Web: “open” data and links Painting Painter“Green Stripe (Mme Matisse)” “Henri Matisse”Royal Museum of Fine Arts, Copenhagen Getty ULAN creator Dublin Core URL Web link URL 4
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  6. 6. Principle 1: semantic annotationDescriptionof webobjects with“concepts”from asharedvocabulary 6
  7. 7. Principle 2: semantic search Query• Search for “Paris” objects which are linked via Paris concepts (semantic link) PartOf• Use the type of semantic link to provide Montmartre meaningful presentation of the search results 7
  8. 8. Principle 3: vocabulary alignment “Tokugawa” AAT style/period SVCN period Edo (Japanese period) Edo Tokugawa AAT is Getty’s SVCN is local in-houseArt & Architecture Thesaurus ethnology thesaurus 8
  9. 9. The myth of a unifiedvocabulary• In large virtual collections there are always multiple vocabularies – In multiple languages• Every vocabulary has its own perspective – You can’t just merge them• But you can use vocabularies jointly by defining a limited set of links – “Vocabulary alignment”• It is surprising what you can do with just a few links 9
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  12. 12. Part of the Dutch national MultimediaN project CWI, VU, UvA, DEN, ICN Alia Amin, Lora Aroyo Mark van Assem, Victor de Boer Lynda Hardman Michiel Hildebrand, Laura HollinkMarco de Niet, Borys Omelayenko Marie-France van Orsouw Jacco van Ossenbruggen Guus Schreiber, Jos Taekema Annemiek Teesing, Anna Tordai Jan Wielemaker, Bob Wielinga Rijksmuseum Amsterdam Dutch ethnology musea (Amsterdam, Leiden)National Library (Bibliopolis) 12
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  14. 14. Extra slides 14
  15. 15. From metadata tosemantic metadata 15
  16. 16. Example textualannotation 16
  17. 17. Resulting semantic annotation(rendered as HTML with RDFa) 17
  18. 18. Levels of interoperability• Syntactic interoperability – using data formats that you can share – XML family is the preferred option• Semantic interoperability – How to share meaning / concepts – Technology for finding and representing semantic links 18
  19. 19. Term disambiguation is keyissue in semantic search• Post-query – Sort search results based on different meanings of the search term – Mimics Google-type search• Pre-query – Ask user to disambiguate by displaying list of possible meanings – Interface is more complex, but more search functionality can be offered 19
  20. 20. Semantic autocompletion 20
  21. 21. Faceted (pre query) Faceted search 21
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  25. 25. skos 25
  26. 26. •v 26
  27. 27. Multi-lingual labels forconcepts 27
  28. 28. Learning alignments• Learning relations between art styles in AAT and artists in ULAN through NLP of art historic texts – “Who are Impressionist painters?” 28
  29. 29. Perspectives• Basic Semantic Web technology is ready for deployment• Web 2.0 facilities fit well: – Involving community experts in annotation – Personalization, myArt• Social barriers have to be overcome! – “open door” policy – Involvement of general public => issues of “quality” 29
  30. 30. Semantic interoperability• Large, smart web “mash ups”, combining: – Data: images, metadata & encyclopaedic knowledge (gazetteers, thesauri, Wikipedia, …) – Visualisations: maps, timelines, social networks, …• Data too diverse for a traditional database approach – fixed schemas will not work – data includes relational data, XML text, images, video, …• Need to link different data sources together – focus on light weight, heuristic approaches – reusing as much as possible (web standards)• Need new interfaces and search paradigms – need to find relations between pieces of information – need to organize (cluster/rank/filter) the many relations we will find 30
  31. 31. Caveats for museumsoftware• Be wary of Flash – Accessibility• Make sure you can connect others and other can connect to you – “Don’t buy software which does not support standard open API’s”• Export facilities to common formats (XML, …) 31
  32. 32. Semantic Web Myths *)• Sem Web = Artificial Intelligence on the Web• Relies on centrally controlled ontologies for “meaning” – as opposed to a democratic, bottom-up control of terms• One has to manually add metadata to all Web pages, relational databases, XML data, etc to use it• It is just ugly XML• One has to learn formal logic, knowledge representation, description logic, etc.• An academic project, of no interest for industry 32*) Adapted from a slide by Frank van Harmelen, panel WWW2006