Linking Folksonomies to Knowledge Organization Systems

1.863 Aufrufe

Veröffentlicht am

Presentation at Metadata and Semantic Research (MTSR), November 30th, 2012.

Veröffentlicht in: Bildung
0 Kommentare
0 Gefällt mir
  • Als Erste(r) kommentieren

  • Gehören Sie zu den Ersten, denen das gefällt!

Keine Downloads
Aufrufe insgesamt
Auf SlideShare
Aus Einbettungen
Anzahl an Einbettungen
Gefällt mir
Einbettungen 0
Keine Einbettungen

Keine Notizen für die Folie

Linking Folksonomies to Knowledge Organization Systems

  1. 1. Linking Folksonomies to Knowledge Organization Systems Jakob Voß (VZG) Metadata and Semantic Research (MTSR), November 30th, 2012
  2. 2. Social Tagging and FolksonomiesWikipedia and Stack ExchangeLinking Folksonomies to KOSResults
  3. 3. Section 1Social Tagging and Folksonomies
  4. 4. Social Tagging Keywords/tags manually assigned to documents by members of a distributed community of volunteers Tags freely chosen (or easy to create new) Outcome of tagging activity in a tagging system: Folksonomy
  5. 5. Properties of Social Tagging Tagging systems are very dynamic — especially compared to normal KOS Different types of tagging systems exist: — don’t compare apples and oranges! source of resources tagging rights, tagging support, tag management tag aggregation tag connectivity
  6. 6. Tag aggregation: Bag-Model
  7. 7. Tag aggregation: Bag-Model
  8. 8. Tag aggregation: Set-Model
  9. 9. Tag aggregation: Set-Model
  10. 10. Folksonomies in set-model tagging systems Dynamic knowledge organization systems created by communities of distributed volunteers Directly given as snapshot of community consensus Limited awareness among community members Two popular examples: Categories in Wikipedia Tags in Stack Exchange
  11. 11. Section 2Wikipedia and Stack Exchange
  12. 12. Categories in Wikipedia
  13. 13. folksonomy is a thesaurus
  14. 14. Tags in Stack Exchange tags in a question anyone can edit tags (after a while) folksonomy is a flat file of keywords (with some synonyms)
  15. 15. Section 3Linking Folksonomies to KOS
  16. 16. Knowledge Organization Systems (KOS) Classifications, thesauri, taxonomies, authority files. . . Common model of KOS for exchange and interlinking: Simple Knowledge Organization System (SKOS): <> a skos:Concept ; skos:broader <> ; skos:narrower <> ; skos:related <> ; skos:exactMatch <> ; skos:closeMatch <> .
  17. 17. Harvest and SKOSify folksonomy
  18. 18. Additional links from tag names Reuse of Computing Research Repository (CoRR) notations
  19. 19. Mapping to CoRR classification @prefix cst: <> . [ skos:notation "LO"; skos:prefLabel "Logic in Computer Science"@en ] skos:closeMatch cst:lo.logic . [ skos:notation "DS" ; skos:prefLabel "Data Structures and Algorithms"@en ] skos:narrowMatch cst:ds.algorithms , .
  20. 20. Feedback of enrichment and links into the community
  21. 21. Enrichtment of tag description in Wikipedia
  22. 22. Enrichtment of tag description in Wikipedia <> a skos:Concept ; skos:prefLabel "H¨rspiel"@de ; o skos:narrowMatch <> , <> ; skos:closeMatch <> , # DDC <> . # GND
  23. 23. Enrichtment of tag description in Stack Exchange
  24. 24. Enrichtment of tag description in Stack Exchange @prefix libse: <> libse:ils a skos:Concept ; skos:broader libse:software ; skos:narrower libse:circulation> , libse:collection-management , libse:cataloging> , libse:opac ; skos:closeMatch <> <> , <> , <> .
  25. 25. Feedback of enrichment and links into the community Feedback with additional benefit: find related documents One must be able to directly link to a rich collected of documents indexed with the concept notation/identifier of each KOS
  26. 26. Section 4 Results
  27. 27. hierarchical links
  28. 28. Mappings to other KOS Published in SKOS/RDF as shown Simple mappings in form of BEACON files #PREFIX: #RELATION: ils| ils| ils| ils| archives|
  29. 29. Outcome and Benefits Show related documents guide people from communities to collections Catalog enrichment guide people from collections to communities Collection analysis
  30. 30. Compare collections with measuring at one KOS Collection of papers at compared to question at theoretical computer science Stack Exchange: complexity theory is asked much more then published information theory is published much more then asked about
  31. 31. References Scripts and data harvested available at Source of paper and slides available at Both Wikipedia and Stack Exchange data available under CC-BY-SA accessible via open APIs: Icons CC-BY based on