Exploring Linked Data

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  • Faceted view for Species > Bird Looking for pigeons (Columbidae) in “Mediterranean Countries”… Filter on direct properties like Familia = Columbidae
  • No “Mediterranean Countries” in Geo facet…
  • Use the pivot operation to filter Populated Places connected through the Geo facet…
  • Faceted view for Populated Place, previous filters are kept
  • Scroll down to the Subject facet, select “Countries of the Mediterranean Sea”
  • The Countries in the Mediterranean Sea that have Birds in the Columbidae family, pivot back to Bird to get the list of Birds
  • Showing the Birds in DBPedia part of the Columbidae family and located in Populated Places related with the “Countries of the Mediterranean Sea” topic
  • Exploring Linked Data

    1. 1. Exploring Linked Data Roberto García Lotico Semantic Web Meetup San Francisco, August 8th 2012Human-Computer Interaction Universitat de Lleida and Data Integration Spain Research Group
    2. 2. Who• Associate Professor, Universitat de Lleida, Spain• Visiting Associate Professor, Standford University – Stanford HCI Group• +12 years Semantic Web research – 1999 MSc Thesis: Knowledge Management using RDF plus reasoning (SiLRI) – 2006 PhD Thesis: A Semantic Web approach to DRM – 2006- Copyright Ontology – 2007- Lleida HCI Group, Semantic Web User Interfaces
    3. 3. Tons of semantic data…http://linkeddata.org
    4. 4. Fine for computers… but people? M. Harper (developer) I’m developing a bird watching application. Can I reuse DBPedia?http://linkeddata.org
    5. 5. Proposal Ontologies and dataset structureAutomatic UI Generation Information Architecture Components [Morville] Overview Menus, Sitemaps,…InteractionPatterns for Zoom & Filter FacetsData Analysis [Shneiderman] Details Lists, Maps, Timelines…
    6. 6. IA Components. Menus7 menus with 10 submenus Automatic Generation
    7. 7. DEMO http://rhizomik.net/dbpedia/ IA Components. MenusDBPedia overview… …but what about 12.334 birds?
    8. 8. IA Components. Facets• Pre-computed list of facets / class or topic – Ontologies, Thesaurus + instance data – Facets for all inverse properties (explicit or implicit) • Actor  actor – Film: – Actor has facet “is actor of Film” – Pivoting: switch from faceted view to related faceted views (keeping filters) • E.g.: from Birds facets to Places facets through the “geo” facet
    9. 9. DEMOhttp://rhizomik.net/dbpedia/
    10. 10. DEMO http://rhizomik.net/linkedmdb/ Conclusions• Users build queries without SPARQL or dataset structure knowledge• Example: – Who has directed more films in Oceania? SELECT DISTINCT ?r1 WHERE { ?r1 a movie:Director . ?r2 movie:director ?r1 . ?r2 a movie:Film. ?r2 movie:country ?r3 . ?r3 movie:country_continent ?r3var0 FILTER(str(?r3var0)="Oceania") }
    11. 11. Example: OMediaDis project• Explore dataset about works, recordings, licenses,…• Integrate visualisation plugins – Timeline, map, license viewer,…
    12. 12. Thanks for your attention Roberto García http://rhizomik.net/~roberto roberto.garcia@udl.catHuman-Computer Interaction and Data Integration Universitat de Lleida Research Group

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