Using Linked Data: American Art Collaborative, Oct. 3, 2016
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Linked Data is a interesting topic in museums, but how do we actually use it? This talk profiles several ways the Carnegie Museum of Art uses Linked Data, and talks about when and where Linked Data can be useful.
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Using Linked Data: American Art Collaborative, Oct. 3, 2016
- 1. Using Linked Data American Art Collaborative, October 3, 2016 David Newbury Lead Developer, Art Tracks Carnegie Museum of Art
- 2. Let's talk about provenance.
- 3. Why Linked Data? • Thesauri & Vocabularies • Reconciliation and Hydration • Making connections • Knowledge Representation
- 4. Carnegie Museum of Art • Vocabularies in our CMS • International Party Locater • Archives Site • Art Tracks
- 5. AAT Vocabulary in our CMS Party lookups from ULAN Techniques from AAT
- 7. International Party Locater Add new parties based on ULAN and VIAF records
- 8. Live Demo
- 9. CMOA Archives Site Our first major Linked Data project.
- 10. CMOA Archives Site Finding aids? Not that compelling.
- 12. CMOA Archives Site People and connections? Fascinating.
- 14. Art Tracks Linked Data for Museum Provenance
- 18. museum_provenance library https://github.com/cmoa/ museum_provenance MIT License, standalone Ruby library. v. 0.1.1
- 19. Elysa A UI tool for museum professionals.
- 27. Why Linked Open Data? It's hard. It's confusing. Is it necessary?
- 28. Three uses for Linked Data: • Linking to authorities • Merging knowledge across institutions • Representing dense social and temporal networks
- 29. Linking to authorities An easy sell... ...but doesn't require you to use linked data.
- 30. Merging knowledge across institutions
- 31. Merging knowledge across institutions
- 32. Representing dense social and temporal networks
- 33. Representing dense social and temporal networks
- 34. Representing dense social and temporal networks
- 35. Lessons Learned There are things that you can do with this that are much harder to do any other way. BUT • Linked Data is hard. • If you only want to do one thing with this data, don't do this. • The knowledge that we want to use, we don't have. • We need better tools.