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Linked Open Data in Libraries, Archives & Museums


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Slides from talk at NYPL Labs Brown Bag, July 12, 2011.

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Linked Open Data in Libraries, Archives & Museums

  1. 1. Linked Open Data in Libraries, Archives and Museums Jon Voss – July 12, 2011 – NYPL Labs
  2. 2. Open DatainLibraries, Archives & MuseumsNew York Public Library @jonvossJuly 12, 2011Jon VossHistorypin Strategic Partnerships
  3. 3. Welcome• Goal: a solid, basic, conceptual understanding of Linked Open Data• A chance to collaborate with others, share knowledge, expertise, perspective; explore ideas
  4. 4. Linked Open Data in Cultural Context• It’s not just Libraries, • http:// Archives & Museums• Linked Open Data has evolved in the cultural context of shared information, music, movies• From rock to rap to hip-hop to mashups• Changing expectations from audiences, curators, technologists
  5. 5. History & Mashup Culture +2010 National Archives Photo Contest
  6. 6. 2009 Linked Open Dataphotos by PhOtOnQuAnTiQuE, TED
  7. 7. Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch.
  8. 8. LODLAM is a Growing Movement• in its infancy, but picking up steam• it requires experimentation• small, niche, domain-specific implementations• use cases, reasons for content providers to get excited about contributing
  9. 9. LODLAM is a product of our increasingly connected culture.• it’s an unfolding story, but it’s awn...• first funded projects in the US exploring Linked Open Data in the humanities now underway: • June 2-3, 100 people gathered from around the world to forward LODLAM in the next year
  10. 10. LODLAM is a product of our increasingly connected culture.• and that’s just the beginning... Linked Open Data
  11. 11. Linked
  12. 12. Going from Tables to Graphs
  13. 13. Going from Tables to Graphs • nodes and links in a graph
  14. 14. Going from Tables to Graphs• As computing power increases, the ability to build more and more complex graphs becomes a reality.• Human vs. Machine readable msulibraries lookbackmaps msulibraries internetarchive msulibraries librarycongress lookbackmaps internetarchive internetarchive librarycongress
  15. 15. Introducing Triples Nodes & Links follows jonvoss NYPL_Labs• Quite simply: Subject, Predicate, Object• gives us the ability to describe entities in a way that is machine readable
  16. 16. What do we know about the person: Ed Summers (aside from the fact that he rocks)?Bio: Hacker for libraries, digital archaeologist, pragmatist. bio knows depiction of knows
  17. 17. Triples for machines• triples can be serialized in many different ways, including Resource Description Framework, RDF/XML, RDFa, N3, Turtle, etc, but they all describe things in the <subject><predicate><object> format.• of course, we need to be consistent and predictable for machines to understand us.
  18. 18. • we’re almost ready to talk to machines
  19. 19.
  20. 20. • consider graph demo:• Civil War vocabulary, or a way to link and traverse across datasets • Regiments, battles, Freebase military schema• Building apps • How tools like Simile/Exhibit can use Linked Data in coordination with Freebase (Conflict History:
  21. 21. Now that we can see the code...• Books• Photos• Information
  22. 22. Tim Berners-Lee’s 4 rules of Linked Data• Use URIs as names for things• Use HTTP URIs so that people can look up those names.• When someone looks up a URI, provide useful information, using the standards (RDF*, SPARQL)• Include links to other URIs. so that they can discover more things.
  23. 23. Tim Berners-Lee: 5 Stars of Linked Data• More thanks to Ed Summers: journal/2010/06/04/the-5-stars-of-open-linked- data/• This is NOT all or nothing
  24. 24. A cautionary word about vocabularies
  25. 25. A cautionary word about vocabularies• Caution: what libraries call vocabularies is not necessarily what we mean...• This is how we organize information and triangulate the data we’re looking for• How we agree on predicates• Ontologies like FOAF, OWL,, VIAF, etc.
  26. 26. In summary Linked• Graphs• Human AND Machine readable• Vocabulary, agreed terms for organizing info• Triples, RDF
  27. 27. The “Open” part of Linked Open Data Open• Considerations and ramifications• Difference between shared, published, open• Legal tools• Precedents/Examples
  28. 28. Expose yourself, be vulnerable• This is the major cultural shift, the tide rising amongst institutions, that data wants to be free in a culture economy.• There is value in sharing• It does require a leap of faith, but risks and rewards should be carefully considered and calculated• Excellent resource: JISC Open Bibliographic Data Guide
  29. 29. What will happen to your data?• If you want people to do something with your data/metadata, you have to put it out there• But once you do, it’s [mostly] out of your control. Yet it can be a part of something much greater than any of the component parts• Roots and Wings• Lessig: Humility of the Web
  30. 30. What will happen to your data?• working with Open Data from NOAA at wherecamp 2011.
  31. 31. Metadata vs. data, assets, digital surrogates• A key conceptual shift with Open Data is looking at metadata and data as two separate things, that can have different licensing and permissions
  32. 32.
  33. 33.
  34. 34. What are the legal tools for publishing Open Data?
  35. 35. Legal Tools•• Open Data Published Data CC-BY CC-BY-NC-ND CC0 CC-BY-NC Public Domain Mark CC-BY-NDPublic Domain Dedication and License (PDDL) CC-BY-SAAttribution License (ODC-By)Open Database License (ODC-ODbL) CC-BY-NC-SA
  36. 36. Concerns and Limitations• There is some argument about whether or not metadata can be protected under copyright at all. Copyright protects a creative work, and some argue that metadata is scientific fact, rather than creative work.• Databases are protected differently in the EU and US, for example.• Public Domain and No Known Copyright...• Issuing blanket copyright over all works on a website, even though some may be in the public domain
  37. 37. Examples and precedents• Bibliographic data: • British Library (CC0), University of Michigan (CC0), Stanford (CC-BY) have published large, raw datasets of bibliographic data they have created (being careful not to publish OCLC or other vendor controlled or licensed metadata)
  38. 38. Examples and precedents• Civil War Data 150 • Metadata from contributing federal institutions are largely considered to be Public Domain. • State, local, university & individual researchers are considering policies for metadata publishing on a case by case basis.
  39. 39. Examples and precedents
  40. 40. Sciences leading the way vs. Humanities• In the sciences, there have been a lot of advances in the realm of Open Data, which will provide models for humanities research as well • Nano Publishing: the idea of publishing datasets separately from research findings, so that it can more easily be built upon and integrated into other datasets. Several scientific journals have already started this. • Federally funded medical research must have a data management plan and some funders are requiring that data be published separately from analysis and findings as Open Data
  41. 41. In summary Open• put it out there...• published, shared, and/or open• tools• metadata vs. assets
  42. 42. Google Refine• A tool for large datasets, cleaning and reconciling•• Extremely powerful, though scripting language has not yet been very well documented.• Enables you to reconcile data against the 20 million + known entities in Freebase
  43. 43. What Would You Do?• Conceptualizing domains, Linked Open Data projects, collaborations, etc
  44. 44. Join the LODLAM movement• #lodlam hashtag on Twitter•• proceedings online and on the road for the next year at various annual meetings and conferences• Contribute!
  45. 45. Thanks @NYPL_Labs Team @edsu & crewSloan Foundation, NEH, Internet Archive Historypin & all y’all.