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On Libraries & Linked Data

On Libraries & Linked Data

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On Libraries & Linked Data

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  1. On Libraries & Linked Data Antoine Isaac UB Utrecht, April 6, 2011

  2. Who am I? • Europeana • Web & Media Lab, Vrije Universiteit Amsterdam • W3C Library Linked Data group • (2006-2009) W3C Semantic Web Deployment group SKOS aisaac@few.vu.nl

  3. Demo Following one’s nose to subject heading lists as linked data • American LCSH http://id.loc.gov/authorities/sh85145447#concept • French RAMEAU http://stitch.cs.vu.nl/vocabularies/rameau/ark:/12148/cb11931913j • German SWD http://d-nb.info/gnd/4064689-0 • Agrovoc http://aims.fao.org/aos/agrovoc/c_8309 • STW http://zbw.eu/stw/descriptor/14188-0 • Further on to DBPedia http://dbpedia.org/resource/Water

  4. Demo (fallback option) Subject heading lists as SKOS linked data • American LCSH http://id.loc.gov • French RAMEAU: http://stitch.cs.vu.nl/rameau • German SWD: http://d-nb.info/gnd/ • mapped using manual links from the MACS project http://macs.cenl.org Starting from http://id.loc.gov/authorities/sh85014310#concept

  5. Linked Data? 1. Use URIs as names for things 2. Use HTTP URIs so that people can look up those names 3. When someone looks up a URI, provide useful information using standards (RDF, SPARQL) 4. Include links to other URIs, so that they can discover more things Tim Berners-Lee, http://linkeddata.org/

  6. (Linked) Data Representation • That subject heading data follows a link-intensive data model Uniform resource identifiers (URI) Resource Description Framework (RDF)

  7. (Linked) Data Representation • Use more-or-less the same standard vocabulary Simple Knowledge Organization System (SKOS) http://www.w3.org/2004/02/skos/ For representing thesauri, classifications, etc. on the Semantic Web

  8. A SKOS graph animals cats UF domestic cats RT wildcats BT animals SN used only for domestic cats domestic cats USE cats wildcats

  9. SKOS mappings SKOS provides conceptual links to bridge across different contexts KOS 2: animal human object KOS 1: animals cats wildcats

  10. Links in the data

  11. Links in the data

  12. Growing interest for linked data in the library community

  13. Linked Library Cloud beginning 2008 [Ross Singer, Code4Lib2010] http://code4lib.org/conference/2010/singer

  14. Linked Library “sector” in 2010 Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/

  15. Libraries and LD, the perfect match? • Libraries have been producing (meta)data for ages • Libraries (often) produce high-quality metadata

  16. Libraries and LD, the perfect match? • Library metadata was locked in record silos • But it maintain links to the outside world • Bibliographic and web references • Shared vocabularies • Same books!

  17. Libraries and LD, the perfect match? LD is about • Citing object • Linking to them • Re-using data Think of web-native union catalogues

  18. A vision for the Dutch National Library Johan Stapel, Koninklijke Bibliotheek (now bibliotheek.nl)

  19. A web of cultural heritage data? ?

  20. ?

  21. The current portal

  22. Towards semantic search: facets

  23. 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, flat interoperability format Quick-win quickly showing its limits

  24. 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…

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

  26. 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

  27. Europeana Data Model Trying to evolve towards RDF and Linked Data • Representing objects, persons, places, etc. as resources • Linking and re-using external sources • (Re-using) richer data modeling features SKOS, CIDOC-CRM, OAI-ORE • Enabling domain-specific data profiles • Separating original data from enrichments http://version1.europeana.eu/web/europeana-project/technicaldocuments/

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

  29. Clustering of results

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

  31. A "more specific Egypte"?

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

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

  34. Following other relations

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

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

  37. Enabling bits & pieces Exploiting semantic links in CH vocabularies 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

  38. Challenge #1: Linking

  39. Challenge #1: Linking Manual mapping of large vocabularies is labour-intensive • LCSH, RAMEAU and SWD mapped in the MACS project http://macs.cenl.org • SWD and DDC mapped in the CRISS-CROSS project http://linux2.fbi.fh-koeln.de/crisscross/ Automatic linking is not perfect but can help • STW, AGROVOC… • Some studies (and further pointers) for automatic library thesaurus alignment in the STITCH project http://stitch.cs.vu.nl

  40. Challenge #1: Linking • (Semi-)automatic techniques are necessary to • Connect objects to vocabularies (esp. for legacy data) • Connect objects themselves together • Crowdsourcing? • Making the way librarians create metadata evolve?

  41. Linking strategy for libraries?

  42. Linking strategy for libraries? • Links to library-originated sources • VIAF, LCSH, DDC, UDC, Worldcat, PND… • Links to resources from cultural environment • Museums, archives • Scientific communities: bibliographic data & research data • Publishers • Europeana and other aggregators

  43. Semantic Annotation

  44. Conclusion? • Linked Data won’t not solve everything right now • Just a set of techniques and a vision for better sharing, cross-linking and re-use data, fitting the web • Which is not bad!