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© UNIVERSITETETS SENTER FOR INFORMASJONSTEKNOLOGI UNIVERSITETET I OSLO USIT Side 1 Knowledge organization with TopicMaps Thomas Flemming, web-gruppa USIT.

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Presentation on theme: "© UNIVERSITETETS SENTER FOR INFORMASJONSTEKNOLOGI UNIVERSITETET I OSLO USIT Side 1 Knowledge organization with TopicMaps Thomas Flemming, web-gruppa USIT."— Presentation transcript:

1 © UNIVERSITETETS SENTER FOR INFORMASJONSTEKNOLOGI UNIVERSITETET I OSLO USIT Side 1 Knowledge organization with TopicMaps Thomas Flemming, web-gruppa USIT

2 © UNIVERSITETETS SENTER FOR INFORMASJONSTEKNOLOGI UNIVERSITETET I OSLO USIT Side 2 What’s TopicMaps ISO standard data model for knowledge organization –Standard XML interchange file format, query language and constraint language Used for classifications (hierarcial and faceted), thesauri, ontologies etc. Intuitive abstraction: –Everything is a topic (”Einstein”, ”Sponge”, ”person”) –and has assocations (”boy” subclass-of ”person”) –and occurences (homepage:”http://einstein.com” born:”1905”) –and an id (id:http://en.wikipedia.com/wiki/Einstein)

3 © UNIVERSITETETS SENTER FOR INFORMASJONSTEKNOLOGI UNIVERSITETET I OSLO USIT Side 3 Benefits from TopicMaps Create taxonomies, faceted classification and/or thesauri to increase findability of information Extract information from RDBM to TopicMaps Merge TopicMaps if they have common id’s Off the shelf tools available for web apps, search engines, merging, editing and visualisation Suitable for portals, intranets, knowledge repositories

4 © UNIVERSITETETS SENTER FOR INFORMASJONSTEKNOLOGI UNIVERSITETET I OSLO USIT Side 4 Demo Off the shelf webapp: Several portals merged: Publications:

5 © UNIVERSITETETS SENTER FOR INFORMASJONSTEKNOLOGI UNIVERSITETET I OSLO USIT Side 5 Expressivity progression ( from Garshol) No model Closed modelOpen model Topic Maps Taxonomies, thesauri Flat list, tags

6 © UNIVERSITETETS SENTER FOR INFORMASJONSTEKNOLOGI UNIVERSITETET I OSLO USIT Side 6 Knowledge organization (from Pepper) Formal, standardized language Full topic maps Weakly structured Strongly structured Term Lists (flat) Classification and categorization (hierarchical) Ontologies (associative) Natural language TAO topic maps Thesauri Faceted classification Taxonomies Classification schemes Subject headings Synonym rings Authority Lists Controlled Vocabulary Mind Maps

7 © UNIVERSITETETS SENTER FOR INFORMASJONSTEKNOLOGI UNIVERSITETET I OSLO USIT Side 7 TopicMaps is not Semantic Web (from Pepper) RDF/OWL is optimized for inferencing; Topic Maps is optimized for findability. RDF/OWL is based on formal logic; Topic Maps is not based on formal logic. RDF/OWL is to mathematics as Topic Maps is to language.

8 © UNIVERSITETETS SENTER FOR INFORMASJONSTEKNOLOGI UNIVERSITETET I OSLO USIT Side 8 Questions? Thank’s for your attention.


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