Semantic Web and Linked Data for cultural heritage materials Approaches in Europeana

1. Semantic Web and Linked Data for cultural heritage materials Approaches in Europeana Antoine Isaac Vrije Universiteit Amsterdam Europeana DANS Linked Data and RDF workshop, Den Haag, July 28th 2010

2. A web of cultural heritage data? ?

3. ?

4. The current portal

6. Towards semantic search: facets

7. Building a search engine on top of metadata is difficult Intrinsic quality problems: correctness, coverage Especially when data is so heterogeneous 100s of formats From flat 5-fields records to 100-nodes XML trees Language issue! We currently use a simple interoperability format Quick-win showing quickly its limits

8. Semantic ThoughtLab: experimenting solutions We can better use institutions’ original metadata Accommodate their different practices Data structures and semantics Access objects via a semantic layer of vocabularies for subjects, persons, places…

9. Towards semantics-enabled search Building a "semantic layer" to help accessing content

10. Towards semantics-enabled search • Enhance access to Europeana content by semantics • Query expansion, clustering of results • Exploiting various types of relations • "located in", "lived in", "is more specific concept"… • Semantics are already there, in metadata and "controlled vocabularies" used in metadata • Thesauri, classifications… • Requires to make it properly machine-accessible

11. Prototype: Europeana Thought Lab • http://europeana.eu/portal/thought-lab.html

12. Semantic auto-completion

13. Clustering of results

14. Baseline: matching concepts' label Metadata for the object Controlled place name from a vocabulary at the Rijskmuseum

15. A "more specific Egypte"?

16. A "more specific Egypte"? Metadata for the object

17. A place more specific than the Egypt one Semantic information on the Giza place in the Rijskmuseum Vocabulary

18. Following other relations

19. Following other relations - creator Metadata for the object Controlled person name from a vocabulary at the Rijskmuseum

20. Following other relations - match Information on Gustave Le Gray from the Rijskmuseum Vocabulary Matched to a "Gustave Le Gray" from another Vocabulary

21. Following other relations – death place Information on Gustave Le Gray from the Union List of Artist Names (Getty)

22. Following other relations – death place Information on Cairo from the Thesaurus of Geographic Names (Getty) Matched to "Cairo" from another vocabulary…

23. A hell of relations? • Well, they were in the original data, we just had to make them explicit! • Cultural Heritage institution often have a wealth of metadata to share and exploit

24. Enabling bits & pieces Exploiting semantic links in CH vocabularies Rijksmuseum thesaurus: Concept “Giza” narrower than concept “Egypte” Mapping/alignment between CH vocabularies Louvre’s “Égypte” equivalent to Rijksmuseum’s “Egypte” Enrichment of existing metadata The string “Egypt” in a metadata record indicates the concept of Egypt defined in Rijksmuseum thesaurus

25. SKOS, Knowledge Organization Systems and Linked Data SKOS allows representing (simple) KOS data as RDF animals NT cats cats UF domestic cats RT wildcats BT animals SN used only for domestic cats domestic cats USE cats wildcats

26. SKOS, KOSs and LD SKOS allows bridging across KOSs from different contexts http://www.w3.org/2004/02/skos/

27. SKOS is used! • Many Libraries – not a surprise! • Swedish National Library’s Libris catalogue and thesaurus http://libris.kb.se/ • Library of Congress’ vocabularies, including LCSH http://id.loc.gov/ • DNB’s Gemeinsame Normdatei (incl. SWD subject headings) http://d-nb.info/gnd/ Documentation at https://wiki.d-nb.de/display/LDS • BnF’s RAMEAU subject headings http://stitch.cs.vu.nl/ • OCLC’s DDC classification http://dewey.info/ and VIAF http://viaf.org/ • STW economy thesaurus http://zbw.eu/stw • National Library of Hungary’s catalogue and thesauri http://oszkdk.oszk.hu/resource/DRJ/404 (example) • Other fields • Wikipedia categories through Dbpedia http://dbpedia.org/ • New York Times subject headings http://data.nytimes.com/ • IVOA astronomy vocabularies http://www.ivoa.net/Documents/latest/Vocabularies.html • GEMET environmental thesaurus http://eionet.europa.eu/gemet • UMTHES • Agrovoc http://aims.fao.org/ • Linked Life Data http://linkedlifedata.com/ • Taxonconcept http://www.taxonconcept.org/ • UK Public sector vocabularies http://standards.esd.org.uk/ (e.g., http://id.esd.org.uk/lifeEvent/7 )

28. KOS Alignments? Quite many of them are linked to some other resource • LCSH, SWD and RAMEAU interlinked through MACS mappings • GND linked to DBpedia and VIAF • Libris linked to LCSH • Agrovoc to CAT, NAL, SWD, GEMET • NYT to freebase, DBpedia, Geonames • dbPedia links are overwhelming Hungary, STW, TaxonConcept, GND…

29. Enabling bits & pieces (c’ed) Appropriate data model for objects Generic constructs for creation, title, subject, etc. that are useful for querying Flexible data model SW ontology linking features allow to keep close to original data while having the generic notions above

30. ?y vra:subject skos:broader ?x rma:Egypt rma:Cairo rma:depicts skos:broader rma:gezicht_in_cairo rma:Egypt Formal semantics, metadata schemas and querying • The query: • The existing description: • Why is there a match? For the Europeana ontology, every rma:depicts statement implies a vra:subject statement

31. Where are the challenges? • Semantic conversion of data • Using appropriate data models • Enriching legacy metadata • Semantic alignments • Between description ontologies vra:depictsrdfs:subPropertyOfdc:subject • Between concepts in controlled vocabularies iconclass:bird skos:closeMatch ddc:bird

32. Alignment of semantic references

33. Where are the challenges? • Semantic alignment (c'ed) • Find correspondences between large vocabularies • In a multilingual context • Scalability • Plugging the semantic features into the Europeana production environment

34. The Europeana Data Model (EDM) with input from Carlo Meghini, Guus Schreiber, Stefan Gradmann, Maxx Dekkers, Steffen Hennicke, Viktor de Boer et al. from Europeana V1

35. Rationale of EDM • Precursor: ESE (Europeana Semantic Elements) • represents lowest common denominator for object metadata • convert datasets to Dublin-Core like standard • forces interoperability • major drawback: original metadata is lost • most values are simple strings • EDM goals • preserve original data while still allowing for interoperability • Semantic Web representation • A community-driven effort • Core experts, validation by representatives of various CH domains

36. EDM requirements & principles • Distinction between “provided object” (painting, book, program) and digital representation • Distinction between object and metadata record describing an object • Allow for multiple records for same object, containing potentially contradictory statements about an object • Support for objects that are composed of other objects • Standard metadata format that can be specialized • Standard vocabulary format that can be specialized • EDM should be based on existing standards

37. EDM basics • OAI ORE for organization of metadata about an object • Dublin Core for metadata representation • SKOS for vocabulary representation + Links to CIDOC-CRM and other shared ontologies

38. Dublin Core • EDM uses the latest version of DCMI Metadata Terms for a core of semantically interoperable properties • And for backward compatibility, cf. ESE • Specified with an RDF model • Specialization of 15 original DC elements • Can be specialized itself • see requirement -> this is a crucial distinction with ESE • Used in the richest way possible • Pointers to resources

39. SKOS: vocabulary publication on the Web • Already seen…

40. OAI ORE • Specification: http://www.openarchives.org/ore/1.0/toc.html • Specified with an RDF model • Four key notions (RDF classes) • Object: the book/painting/program being described • Aggregation: organizes object information from a particular provider (museum, archive, library) • Proxy: the object as viewed in a metadata record • Digital representation: some digital form of the object with a Web address

41. The Example - 1

42. The Example - 2

43. Aggregation organizes data of a provider digital representation provenance metadata aggregation object

44. Proxy: metadata record for an object object metadata proxy

45. Multiple aggregations = multiple providers aggregation of DMF aggregation of Louvre

46. Multiple aggregations = multiple providers DMF proxy DMF title The “real” painting Louvre Proxy Louvre title

47. Europeana is “just” a special providerwith processed/enriched metadata Europeana aggregation enriched metadata Europeana landing page

48. A flexible model: different semantic grains • Cf. goal: “preserve original data while still allowing for interoperability” • Keep data expressed as close as possible to original model • Using mappings to more interoperable level

49. A flexible model: objects, events and the rest • Preserving and exploiting original data also means being compatible with descriptions beyond simple object level • Also crucial for semantic enrichment

50. A flexible model: object and events (2) • Classes and Properties for event-, agent-, place-centric modeling • Instances of (local) vocabularies using skos:Concept • Using RDF, EDM allows any kind of network to be attached to a provided object.