New OrleansNovember 16-17, 2015 Expanding Machine-Readable Access Methods for Collections Tearing Down Data Silos with Linked Open Data Eleanor E. Fink, Manager, American Art Collaborative

1. New Orleans
November 16-17, 2015
Expanding Machine-Readable Access Methods for
Collections
Tearing Down Data Silos
with
Linked Open Data
Eleanor E. Fink, Manager
American Art Collaborative

2. Eleanor E. Fink
Linked Open Data
•A method of publishing structured data so
that it can be interconnected and become
more useful.
•Uses a mark up language called RDF. When
combined with a domain ontology the
relationship between subject, predicate, and
object can be tagged explicitly.
•As a result when you are searching using LOD
you don’t get the “noise” or unrelated
information you get with online searching.

3. Linked Data
facts:
<subject> <predicate> <object>
using W3C standards (RDF)
links between facts from different databases
like links between Web pages
Pedro Szekely and Craig KnoblockUniversity of Southern California
Eleanor E. Fink

4. A Google search for “winslow homer theft”
retrieves documents that users must read to
extract relevant information
information

5. Interlinked LOD resources relevant to
locating stolen or looted cultural property

6. Eleanor E. Fink
American Art Collaborative LOD

7. Window to the World of Knowledge

8. Eleanor E. Fink
Tear Down Data Silos
Provide Open Access

9. American Art Collaborative
Eleanor E. Fink
Consortium of museums who have come
together to learn about and implement LOD
within their respective museums. AAC is
developing its LOD under a federated model
whereby each AAC member assumes
responsibility for updating and maintaining
its own data.
http://americanartcollaborative.org/

10. AAC Partners
•Amon Carter Museum of American Art
•Archives of American Art, Smithsonian Institution
•Autry National Center
•Colby College Museum of Art
•Crystal Bridges Museum of American Art
•Dallas Museum of Art (DMA)
•Indianapolis Museum of Art (IMA)
•Thomas Gilcrease Institute of American History and Art
•National Portrait Gallery, Smithsonian Institution
•National Museum of Wildlife Art
•Princeton University Art Museum
•Smithsonian American Art Museum (SAAM)
•Walters Art Gallery

11. Andrew W. Mellon Foundation
Planning Grant
American Art Collaborative Linked Open
Data Initiative (AAC)
Education
Mission Statement
Commitment
Road Map
Eleanor E. Fink

12. IMLS Leadership Grant
Matching Grant Pending
Road Map over next 12- 21 Months
• Convert data to LOD using the CIDOC CRM
• Link to the Getty Vocabularies as well as contribute
missing names to enhance the vocabularies
• Implement an API and reader compliant with the
International Image Interoperability Framework (IIIF)
that will allow researchers to compare and contrast
AAC LOD
• Develop several open source tools including a link
curation tool and IIIF/CRM translator
Eleanor E. Fink

13. • Develop browse demonstration
• Open access
• Link to other LOD nodes (DPLA, Research
Space, Europeana)
• Publish best practices and lessons learned
Eleanor E. Fink

14. Rationale
Eleanor E. Fink
•Learn together as a collaborative; build a
critical mass to explore and demo value of LOD
•As primary holders of art objects and data AAC
members want to make sure LOD is accurate
•More precise results when searching(Semantic
Web)
•Build richer contexts for inquiry by integrating
data from different sources

15. •Interest in access across the partnership as
well as linking to other LOD nodes: providing
more knowledge than any single institution
•Cross domain searching as a window to the
world of knowledge
•Greater visibility; more outreach
•Collaborative platform potential (curator to
curator)
Eleanor E. Fink

16. LOD Data Conversion
via Karma (USC, ISI)
• Karma, open source, semi-automated, data
integration tool that makes LOD conversion
easy
• Initially developed by ISI for the Intelligence
Advanced Research Projects Activity (IARPA).
Now has been applied to 44,000 records from
SAAM and several other museums
• Self learning (learns from patterns with each
mapping)

17. Karma
• Can accept data in all major formats including
spreadsheets, and XML
• Works with any ontology that a client chooses
• High accuracy rate (SAAM over 95% matching
score)
• Staff can interact with tool to make
adjustments
• Scales to large databases

19. CIDOC CRM ontology
82 classes and 263 properties including
relationships
Events
(e.g., creation, production, attribute
assignment),
Immaterial things
(e.g., information objects, appellations,
rights)
Material things
(e.g., actors, physical things, man-made
objects)
Eleanor E. Fink

20. Eleanor E. Fink

21. Slide by Design for Context

22. AAC Vision

23. Thank You
eleanorfink@earthlink.net