1. Use cases Gordon Dunsire

2. UC: Bibliographic network +Identification and deduplication of library records +Regional catalogue +Data BNF +*Community Information Service +?Polymath Virtual Library +*Collecting material related to courses at The Open University +**Collaboration between linked data and legacy library applications (Uldis Bojars)

3. Use cases (Bib network) Bib Network: Use FRBR model to bring together metadata components from different records Identification/deduplication: Need matching algorithms Regional catalogue: Bringing together holdings from multiple libraries

4. Bib network Heterogeneous library catalogue records – User wants a homogeneous resource discovery interface Heterogeneous metadata from other relevant sources – Archives, museums, publishers, sellers, social networks Linked-data breaks different “record” packages into component parts – Makes interoperability easier – differences isolated at low level of granularity Need RDF models for records to disaggregate into instance triples – FRBR, RDA, ISBD

5. Bib network Main barriers become identity and authority (over to Karen) Matching triple properties – Matching URIs – Equality, sub-properties Identification of triple subjects and objects – Objects => authority control Inferencing may help – But properties must be constrained with domains/ranges and OWL properties

6. UC: Language technology +Component vocabularies +Browsing and searching in data repositories annotated with different thesauri

7. Language technology Different library communities use different terminologies for metadata records – “Access” points (subjects, mainly) Differences include: – Language (resource discovery in a multilingual environment) Language of metadata; language of user – Monolingual terminologies (LCSH, AAT, etc.) – Terminologies vs notations – Natural language variants (word stems, plurals, etc.)

8. Language technology Need to link terms from different vocabularies – “Translates” user input into terminologies of metadata Linked-data allows term-by-term matching – Where vocabulary allows – Issue with compound vs simple terms Broader/narrower Part/whole

9. “Translation” architectures One2one – Scalability is an issue (combinatorial explosion) Hub-spoke – More efficient – Issue is what is the hub? Examples (not in use cases) – Vocabulary Mapping Framework (hub-spoke) – High-level thesaurus (hub-spoke) – Multilingual Access to Subjects (one2one) Produced Rameau/LCSH mappings in LOD

10. UC: Library address data Libraries should publish information about themselves to allow identification – Could include collection-level data – Addresses, access conditions