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Scalable Identifiers for Natural History Collections


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Scalable Identifiers for Natural History Collections

  1. 1. Scalable Identifiers for Natural History Collections 12 August 2012 University of California Curation Center California Digital Library
  2. 2. California Digital LibraryServing the University of California• 10 campuses• 360K students, faculty, and staff• 100’s of museums, art CDL supports the research galleries, observatories, marine lifecycle centers, botanical gardens • Collections• 5 medical centers • Digital Special Collections• 5 law schools • Discovery & Delivery• 3 National Labs • Publishing Group • UC Curation Center (UC3)
  3. 3. The research data probleman article about data, but no data
  4. 4. What EZID data citation offers• Precise identification of a dataset (DOI, ARK)• Credit to data producers and data publishers• A link from traditional literature to the data• Exposure and research metrics for datasets (Web of Knowledge, Google)
  5. 5. EZID: Long term identifiers made easy Take control of the management and distribution of your research, share and get credit for it, and build your reputation through its collection and documentation
  6. 6. EZID: Long term identifiers made easy Take control of the management and distribution of your research, share and get credit for it, and build your reputation through its collection and documentation
  7. 7. DataCiteGerman National Library of Economics (ZBW)German National Library of Science and Technology (TIB) Canada Institute for Scientific and Technical Info. (CISTI)German National Library of Medicine (ZB MED) Technical Information Center of DenmarkGESIS - Leibniz Institute for the Social Sciences, Germany Institute for Scientific & Technical Information (INIST-Australian National Data Service (ANDS) CNRS), FranceETH Zurich, Switzerland TU Delft Library, The Netherlands The Swedish National Data Service (SNDS) The British Library , UK California Digital Library (CDL), USA Office of Scientific & Technical Information (OSTI), USA Purdue University Library
  8. 8. EZID Clients A current, partial listUC Berkeley Library (on behalf of the UC Berkeley The Digital Archaeological Record (tDAR)campus) Sponsored accounts: Open Context Dryad Digital Repository CRCNS.orgUC San Diego Library (on behalf of the UC San Diego Fred Hutchinson Cancer Research Centercampus)American Astronomical Society(AAS) LabArchivesCentre national de documentation National Center for Atmospheric Research (NCAR)pédagogique(CNDP)Cornell Institute for Social & Economic USGS/Earth Sciences Data ClearinghouseResearch (formerly National Biological Info. Infrastructure)
  9. 9. New features in development• Suffix pass-thru: do NT and get N/ST/S for free• Service replicas: manager and resolver• Content negotiation and inflections: ? ?? / .• URN (Uniform Resource Name) support (urn:uuid:)• ARK community and governance, eg, registries
  10. 10. Some identifier dimensions• registration (storing and updating ids for resolution)• non-registration (id awareness via rules)• persistence flavors• resolution• clusters (closely coupled ids)• other relations (part, whole, related)
  11. 11. Identifier generation• inspiration ("I think Ill call it MyKitty/Photos")• systematic inspiration (title/author/vol/issue)• counter (421, 422, 423, ...)• timestamp• hash computed over content (MD5, SHA256)• hash of randomized timestamp plus registry (uuidgen, noid)• randomized counter plus registry (EZID/noid)
  12. 12. Identifier registration• use filesystem tree as resolver (any old website)• use web server config file• use web server backing database• use a service (, EZID, DataCite, local Handle service)
  13. 13. Identifier non-registrationIdentifiers “exposed” but not registered, eg, awareness via rules• extension (abc/def is "part of" abc)• parameter (abc_N_M works for N or M less than 100,000)• general query (arbitrary data cells)
  14. 14. Identifier persistence flavors• persistent id to very dynamic content (eg, home page)• persistent id to stable but correctable content (eg, landing page)• persistent id to never-changing content (eg, spreadsheet) – persistent ids to non-recommended content• persistent id to stable but growing content (serial pub)
  15. 15. Identifier resolution• DNS (domain names)• DNS + HTTP (any website)• DNS + HTTP + redirects (eg, URL shorteners, N2T/EZID system)• DNS + HTTP + redirects + Handle resolver (DOIs and Handles)
  16. 16. Identifier clustersRelated, but very closely couple identifiers• object files• alternate object files• object metadata
  17. 17. GUID Definitions• GUID -- Definition 1 (wikipedia) – A 128-bit id generated per RFC 4122, eg, – uuidgen -> EEF45689-BBE5-4FB6-9E80- 41B78F6578E2• GUID -- definition 2 (earth sciences?) – any globally unique identifier
  18. 18. Service replicas• EZID is an id manager that populates N2T – It tolerates down time – Other id manager services might one day populate N2T• N2T (Name-to-Thing) is an id resolver that ... – It is very intolerant of down time, since it services all access requests for locations and metadata – N2T replicas underway
  19. 19. URN support• N2T and EZID are agnostic about kinds of things, names, and metadata – Digital, physical, abstract, living, fictional, groups, etc. – Any metadata & known profiles (DataCite, Dublin Kernel) – ARK, DOI, URN, Handle, IVOA, LSID, PMID, etc., requiring namespace “write” permission, eg, via DataCite• In test: Uniform Resource Names (URNs) – urn:uuid namespace
  20. 20. Under the hood keysmithing terms:bows, shoulders, blades, tips, covers
  21. 21. Suffix pass-thru: NT gets N/ST/S for freeIdea: if name N points to target T, then requests for N extended by any suffix N/S can take you to T/S• For dataset doi:10.5072/Big4 with 10,000 nameable components, – Register and manage 10,001 names or 1 name? – Eg, http://x.y.z/foo/Big4/db/table/cell/45-8.txt could be reached with doi:1.5072/Big4/table/cell/45-8.txt• In test with ARKs. Conflict with other resolvers?
  22. 22. Tombstone and other surrogate pagesTombstone, incubation, and other surrogate pages (probation?) auto-generated from metadata, eg,
  23. 23. Reserved identifiers and multiple targets• Some ids must be created and managed (reserved) before going public, eg, for manuscript preparation• In test: infrastructure for multiple targets and multiple instances of any metadata element• What should user experience be for multiple targets? – Present a menu of targets (burden of choice)? – One target chosen for them (burden of inflexibility)?
  24. 24. Identifier (ARK) inflections: ? ?? / .• Inflect: change endings w.o. creating new words – Terminal ? means “I want metadata”, which is similar to linked data content negotiation (also in EZID test) – Terminal ?? means “I also want support metadata” – Drawing board: / could mean “I want a landing page” and . could mean “I want the usual computable thing”• Allow inflections beyond ARKs to DOIs/URNs?
  25. 25. Example: Renninger, Heidi; Phillips, Nathan; Hodel, Donald. “Comparative hydraulic and anatomic properties in palm trees (Washingtoniarobusta) of varying heights”. 2009-04-29. ark:/13030/qt0349g1rh HTML content with embedded comments in ANVL/ERC and RDFerc:who: Renninger, Heidi,; Phillips, Nathan,; Hodel, Donald,what: Comparative hydraulic and anatomic properties in palm trees (Washingtoniarobusta) of varying heightswhen: 2009-04-29where: ark:/13030/qt0349g1rh
  26. 26. ARK community and governance• ARK mailing list:• Topics: governance, community, standardization• Registry maintenance: shoulders and NAANs• N2T consortium with alternative EZID-like services