SKOS and Linked Data


Published on

Presentation at ISKO-UK Linked Data: The Future of Knowledge Organization on the Web conference. More at

Published in: Technology
  • Be the first to comment

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide
  • electronic service delivery
  • 32 constructs in total
  • SKOS and Linked Data

    1. 1. SKOS and Linked Data Antoine Isaac ISKO, London, Sept. 14 th 2010
    2. 2. Personal background <ul><li>Europeana </li></ul><ul><li>Web & Media Lab , Vrije Universiteit Amsterdam </li></ul><ul><li>W3C Library Linked Data group </li></ul><ul><li>(2006-2009) W3C Semantic Web Deployment group </li></ul><ul><ul><li>SKOS </li></ul></ul>
    3. 3. Towards a web of culture data
    4. 4. Government data again?
    5. 5. Government data again?
    6. 6. SKOS <ul><li>Simple Knowledge Organization System </li></ul><ul><li>Scope: knowledge organization systems (KOS) such as thesauri, classification systems, subject heading lists… </li></ul><ul><li>SKOS is for representings KOSs in RDF in a simple way </li></ul>
    7. 7. Representing semantics <ul><li>The formal way: OWL Semantic Web ontology language </li></ul><ul><li>Used for ontologies that enable machine reasoning </li></ul><ul><li>Mother is a class </li></ul><ul><li>It is the intersection of the classes Woman and Parent </li></ul><ul><li>Parent is the class of entities of type Person that are related to at least one other resource of type Person using the child property </li></ul><ul><li>… </li></ul>
    8. 8. SKOS is not for formal ontologies <ul><li>Turning KOSs into ontologies is possible, but KOSs </li></ul><ul><ul><li>are large </li></ul></ul><ul><ul><li>have softer “semantics” </li></ul></ul><ul><ul><ul><li>Parent RelatedTerm Child </li></ul></ul></ul><ul><ul><li>have often a focus on terminological information </li></ul></ul><ul><ul><ul><li>Child UsedFor Offspring </li></ul></ul></ul><ul><li>Softer semantics can be useful as such for many applications! </li></ul><ul><ul><li>Semantic search, annotation… </li></ul></ul>
    9. 9. Basic SKOS <ul><li>A set of features common to various KOS types and useful for many applications </li></ul><ul><li>Concepts </li></ul><ul><li>Lexical properties </li></ul><ul><li>Semantic relations </li></ul><ul><li>Notes </li></ul>
    10. 10. Thesaurus example Animals cats UF ( used for ) domestic cats RT ( related term ) wildcats BT ( broader term ) animals SN ( scope note ) used only for domestic cats domestic cats USE cats wildcats
    11. 11. Concepts and labels cats UF ( used for ) domestic cats skos: = rdf: = ex: =
    12. 12. Note: multilingual labels
    13. 13. Semantic relations cats RT ( related term ) wildcats BT ( broader term ) animals
    14. 14. A SKOS graph animals cats UF domestic cats RT wildcats BT animals SN used only for domestic cats domestic cats USE cats wildcats
    15. 15. SKOS mappings <ul><li>SKOS allows bridging across KOSs from different contexts </li></ul>KOS 1: animals cats wildcats KOS 2: animal human object
    16. 16. Other features <ul><li>Concept grouping </li></ul><ul><ul><li>skos:Collection, skos:member… </li></ul></ul><ul><li>Concept documentation </li></ul><ul><ul><li>skos:example… </li></ul></ul><ul><li>SKOS-XL: extension for more complex representation of labels </li></ul><ul><li>Note: SKOS can be extended as any other RDF vocabulary </li></ul>
    17. 17. Semantics for SKOS <ul><li>There are some basic constraints on SKOS data </li></ul><ul><li>E.g., a concept has only one prefLabel per language </li></ul>
    18. 18. Semantics for SKOS <ul><li>There are rules to infer new facts </li></ul><ul><li>E.g., broader and narrower are inverse of each other </li></ul>
    19. 19. Semantics for SKOS <ul><li>Minimal semantic commitment: </li></ul><ul><li>SKOS must cope with existing information and not infer new data beyond what KOS publishers intend </li></ul>
    20. 20. References <ul><li>SKOS Reference </li></ul><ul><li>SKOS Primer </li></ul><ul><li>SKOS homepage </li></ul><ul><li>SKOS wiki </li></ul><ul><li>SKOS mailing list [email_address] </li></ul>
    21. 21. Benefits of SKOS? <ul><li>Easily fitting KOSs into the Semantic Web & Linked Data vision </li></ul><ul><li>Web-oriented representation </li></ul><ul><li>Re-use & sharing of concepts and their descriptions </li></ul><ul><li>Linking between concepts from different contexts </li></ul>
    22. 22. Demo <ul><li>Subject heading lists as SKOS linked data </li></ul><ul><li>American LCSH </li></ul><ul><li>French RAMEAU: </li></ul><ul><li>German SWD: </li></ul><ul><li>mapped using manual links from the MACS project </li></ul><ul><li>Starting from </li></ul>
    23. 28. Linked Data? <ul><li>1. Use URIs as names for things </li></ul><ul><li>2. Use HTTP URIs so that people can look up those names </li></ul><ul><li>3. When someone looks up a URI, provide useful information using standards (RDF, SPARQL) </li></ul><ul><li>4. Include links to other URIs, so that they can discover more things </li></ul><ul><li>Tim Berners-Lee, </li></ul>
    24. 31. SKOS Implementations Miles, Bechhofer, SKOS Implementation Report , May 19th 2009
    25. 32. Some landmark SKOS implementations <ul><li>Swedish National Library’s Libris catalogue and thesaurus </li></ul><ul><li>Library of Congress’ vocabularies, including LCSH </li></ul><ul><li>DNB’s Gemeinsame Normdatei (incl. SWD subject headings) </li></ul><ul><li>BnF’s RAMEAU subject headings </li></ul><ul><li>OCLC’s DDC classification and VIAF </li></ul><ul><li>STW economy thesaurus </li></ul><ul><li>National Library of Hungary’s catalogue and thesauri (example) </li></ul><ul><li>Wikipedia categories through Dbpedia </li></ul><ul><li>New York Times subject headings </li></ul><ul><li>IVOA astronomy vocabularies </li></ul><ul><li>GEMET environmental thesaurus </li></ul><ul><li>Agrovoc </li></ul><ul><li>Linked Life Data </li></ul><ul><li>Taxonconcept </li></ul><ul><li>UK Public sector vocabularies (e.g., ) </li></ul>
    26. 33. KOS Alignments? <ul><li>Quite many of them are linked to some other resource </li></ul><ul><li>LCSH, SWD and RAMEAU interlinked through MACS mappings </li></ul><ul><li>GND -> DBpedia, VIAF </li></ul><ul><li>Libris -> LCSH </li></ul><ul><li>Agrovoc -> CAT, NAL, SWD, GEMET </li></ul><ul><li>NYT -> freebase, DBpedia, Geonames </li></ul><ul><li>dbPedia links are overwhelming </li></ul><ul><ul><li>Hungary, STW, TaxonConcept, GND… </li></ul></ul>
    27. 34. Issues: semantic alignment of SKOS data <ul><li>In a linked data environment, the most interesting applications are the ones that cross contexts </li></ul><ul><li>Mapping data between concept schemes is still scarce </li></ul><ul><li>More efforts are needed </li></ul><ul><ul><li>Automatic or manual or a mixture of both </li></ul></ul>
    28. 35. Issues: linking KOS data to other resources <ul><li>KOSs become valuable when they bring a “semantic layer” over other resources </li></ul><ul><ul><li>E.g. books and the topics they are about </li></ul></ul><ul><li>Existing links are often only implicit in the data—using labels of concepts not their identifiers </li></ul><ul><li>Semantic annotation with KOS should be a main target </li></ul><ul><ul><li>Cf. Drupal’s taxonomy plug-in </li></ul></ul>
    29. 36. Conclusion <ul><li>Publication and linking of linked KOS data is still work in progress, but </li></ul><ul><li>We are now in position of realizing the issues and working towards solving them </li></ul><ul><li>We can start building applications that make use of the wealth of data already available or yet to come </li></ul><ul><ul><li>Many KO resources to re-use and link to </li></ul></ul>
    30. 37. Thank you! [email_address]
    31. 38. Acknowledgements <ul><li>Participants of the Semantic Web Deployment working group </li></ul><ul><ul><li>Alistair Miles, Sean Bechhofer, Ed Summers, Tom Baker, Guus Schreiber… </li></ul></ul><ul><li>Library of Congress </li></ul><ul><li>French National Library </li></ul><ul><li>German National Library </li></ul><ul><li>MACS team (Swiss National Library) </li></ul><ul><li>EuropeanaConnect project </li></ul>