1. eXtended Knowledge Organization System (XKOS) Prepared by Franck Cotton, Institut National de la Statistique et des Études Économiques Daniel W. Gillman, US Bureau of Labor Statistics Yves Jaques, Food and Agriculture Organization of the United Nations 3/2/2016 Work Session on Statistical Metadata (Geneva, Switzerland, 8-10 May 2013) 1

2. Why XKOS? Increasing trend (and pressure) for greater accessibility to public data. Linked Open Data (LOD) among the favored approaches (see data.gov.uk).data.gov.uk but… No existing LOD standards with which to correctly model classifications. XKOS grew from the work on DDI-RDF during several workshops at Dagstuhl organized by GESIS. 3/2/2016 Work Session on Statistical Metadata (Geneva, Switzerland, 8-10 May 2013) 2

3. What is LOD? In 2006 Tim Berners-Lee outlined four principles of Linked Data : Use URIs to identify things Use HTTP URIs so that these things can be referred to and looked up (dereferenced) by people and user agents Provide useful information about the thing when its URI is dereferenced, using standard formats such as RDF/XML Include links to other, related URIs in the exposed data to improve discovery of other related information on the Web 3/2/2016 Work Session on Statistical Metadata (Geneva, Switzerland, 8-10 May 2013) 3 Tim Berners-Lee

4. What is RDF? A standard knowledge model for making statements about resources based on a few elegant ideas: – Everything has a URI. – Knowledge is a series of Subject-Verb-Object statements (triples) 3/2/2016 Work Session on Statistical Metadata (Geneva, Switzerland, 8-10 May 2013) 4 http://xmlns.com/foaf/0.1/Person http://www.example.org/~joe/ mailto:joe.smith@example.org http://www.example.org/~joe/contact.rdf#joesmith http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://xmlns.com/foaf/0.1/homepage http://xmlns.com/foaf/0.1/family_name http://xmlns.com/foaf/0.1/givenname http://xmlns.com/foaf/0.1/mbox JoeSmith

5. What is SKOS? Provides a model for expressing the basic structure and content of concept schemes such as: – thesauri, – classification schemes, – subject heading lists, – taxonomies, – folksonomies, – and other similar types of controlled vocabulary. 3/2/2016 Work Session on Statistical Metadata (Geneva, Switzerland, 8-10 May 2013) 5 “Simple Knowledge Organization System”

6. What does SKOS look like? 3/2/2016 Work Session on Statistical Metadata (Geneva, Switzerland, 8-10 May 2013) 6 skos:ConceptScheme skos:concept skos:prefLabel skos:altLabel skos:definition skos:notation skos:broader skos:narrower skos:related skos:closeMatch skos:exactMatch Concept 6211: Products Concept 8171: Plant Products Concept 1474: Cereals Concept 12332: Maize “Corn”@en “Maize”@en “Kukorica” @hu “Misir”@tr skos:altLabel skos:prefLabel “12332” ^^ skos:notation skos:prefLabel Concept 12332: Zea mays skos:related skos:broaderskos:narrower skos:broaderskos:narrower skos:broaderskos:narrower

7. What is XKOS? 3/2/2016 Work Session on Statistical Metadata (Geneva, Switzerland, 8-10 May 2013) 7 An eXtension of SKOS “eXtended Knowledge Organization System” Derived from the Neuchâtel Model a rdf:List a xkos:ClassificationLevel (level 1) (level 2) a skos:Concept (item 11) a skos:Concept (item 21) a skos:Concept (item 22) a skos:ConceptScheme (classification scheme) xkos:levels skos:member skos:broader skos:topConceptOf skos:inScheme

8. New classes, refined properties 3/2/2016 Work Session on Statistical Metadata (Geneva, Switzerland, 8-10 May 2013) 8

9. Demo 3/2/2016 Work Session on Statistical Metadata (Geneva, Switzerland, 8-10 May 2013) 9

10. Next steps Review the proposal Get feedback from the community Begin W3C submittal process Publicize Implement 3/2/2016 Work Session on Statistical Metadata (Geneva, Switzerland, 8-10 May 2013) 10

11. Thanks. 3/2/2016 Work Session on Statistical Metadata (Geneva, Switzerland, 8-10 May 2013) 11