Is Linked Open Data the way forward?

American Art Collaborative
American Art CollaborativeAmerican Art Collaborative
Back to the Future: Museums and the Web
Is Linked Open Data the way forward?
Professional Forum
Eleanor Fink, American Art Collaborative, USA, Shane Richey, Crystal
Bridges Museum of American Art, USA, Jeremy Tubbs, Indianapolis
Museum of Art, USA, Rebecca Menendez, Autry Museum of the
American West, USA, Cathryn Goodwin, Princeton University, USA
.
1997-2016: Los Angeles, CA.
Tear Down Data Silos
Provide Open Access
Is Linked Open Data the way forward?
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.
A Google search for “winslow homer theft”
retrieves documents that users must read to
extract relevant information
information
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
Is Linked Open Data the way forward?
Is Linked Open Data the way forward?
AAC
Consortium of US 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.
Is Linked Open Data the way forward?
The American Art Collaborative Partners
Amon Carter Museum of American Art, Archives of
American Art, Autry Museum of the American West,
Colby College Museum of Art, Crystal Bridges
Museum of American Art, Dallas Museum of Art,
Thomas Gilcrease Institute of American History and
Art, Indianapolis Museum of Art, National Museum of
Wildlife Art, National Portrait Gallery, Princeton
University Art Museum, Smithsonian American Art
Museum, Walters Art Gallery, and Yale Center for
British Art
Eleanor E. Fink.
American Art Collaborative Advisors
Martin Doerr, Research Director at the Information Systems
Laboratory and head of the Centre for Cultural Informatics
of the Institute of Computer Science, FORTH
Tim Finin, Professor of Computer Science and Electrical
Engineering at the University of Maryland, Baltimore
County
Craig Knoblock, Director of Data Integration, Information
Sciences Institute, University of Southern California
Robert Sanderson, Information Scientist at Stanford
University Libraries
Thorny Staples, Director of the Office of Research
Information Services at the Smithsonian Institution
Andrew W. Mellon Foundation
Planning Grant
American Art Collaborative Linked Open
Data Initiative (AAC)
Education
Mission Statement
Commitment
Road Map
Road Map over next 18 Months
IMLS Leadership Grant
Andrew W. Mellon Foundation Grant
• 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
• Develop browse demonstration
• Open access
• Publish best practices and lessons learned
Panel Discussion Why LOD
•Everyone wants more meaningful content
•Find new ways to share our information and keep
audiences engaged
•To augment our collection information by connecting to
other museums and institutions
•To better support research and improve access
•Achieve seamless access across museums using LOD
•Make our collections more discoverable
•To tell fuller stories about our objects
•Complementarity: e.g. archives about documents
connecting to works of art
•Explore cross domain connections
•LOD makes our data more useable to developers
Why Collaborative
•Learning together
•More comprehensive education
•Building on diverse skills
•Easier to engage and convince management
•Grant Funding to train and produce
•Create best practices
Challenges and Uncertainties
•Licensing
•Mastering the CRM
•Data inconsistencies
•Implications of federated or hybrid models versus
aggregation models
•Learning curve and skill set
•Accuracy of tools
•Working with high end technology experts that
are not art specialists
•As new datasets come online, how to connect
•URI identities and connecting to other resources like
Getty Vocabularies that have their own URI
•How to know what to connect to
•How to make sure you are connecting to the right
entity (person, place, etc.)
•How to maintain the data
•How to obtain metrics on impact of converting your
data to LOD and see how visitors are using your data
•Exploring what openness means
•How to get dpedia to link back
•How do you encourage people to link to your LOD
Challenges and Uncertainties
•How to retain the authority voice about the object
Creative Commons license
E.G.
•Freeing content globally without
restriction CC0
•Only with Attribution CCBY
•Attribution and non commercial CCBY NC
Why Federated Versus Aggregation Model
•Better sustainability model: each responsible
for updating and maintaining like websites
•Vision of Tim Berners Lee (distributed data
residing in a LOD Cloud)
•Richness of data
•Make data openly available for aggregators;
include access nodes to other projects
Is Linked Open Data the way forward?
Is Linked Open Data the way forward?
ISI’s Karma data integration tool
http://isi.edu/integration/karma
Best Practices Guidelines
Eleanor and Diane
W3C G AAC DfC Advisors ISI Emmanuelle SStead
Introduction and Background
includes what AAC identifies as the Initiative’s value added. E.g.
leveraging expertise; being able to address tough technical questions
Challenges
including how to access data using a federated model
Data preparation and mapping
Including licensing, considerations in choosing an ontology, submitting
data, CRM mapping, proofing, how accurate was Karma
Linking and reconciliation issues
Discrepancies in handling of dates, dimensions, etc; multiple URIs
Creating apps (lessons learned browse demo)
IIIF implementation
Hosting
Skills and timeframes
Conclusions and recommendations
Including issues the cultural heritage community will need to address
and consider
American Art Collaborative LOD
Is Linked Open Data the way forward?
“Data that is in motion is much more
preserveable than data on files”
Cory Doctorow
THANK YOU
americanartcollaborative.org/
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Is Linked Open Data the way forward?

  • 1. Back to the Future: Museums and the Web Is Linked Open Data the way forward? Professional Forum Eleanor Fink, American Art Collaborative, USA, Shane Richey, Crystal Bridges Museum of American Art, USA, Jeremy Tubbs, Indianapolis Museum of Art, USA, Rebecca Menendez, Autry Museum of the American West, USA, Cathryn Goodwin, Princeton University, USA . 1997-2016: Los Angeles, CA.
  • 2. Tear Down Data Silos Provide Open Access
  • 4. 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.
  • 5. A Google search for “winslow homer theft” retrieves documents that users must read to extract relevant information information
  • 6. 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
  • 9. AAC Consortium of US 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.
  • 11. The American Art Collaborative Partners Amon Carter Museum of American Art, Archives of American Art, Autry Museum of the American West, Colby College Museum of Art, Crystal Bridges Museum of American Art, Dallas Museum of Art, Thomas Gilcrease Institute of American History and Art, Indianapolis Museum of Art, National Museum of Wildlife Art, National Portrait Gallery, Princeton University Art Museum, Smithsonian American Art Museum, Walters Art Gallery, and Yale Center for British Art Eleanor E. Fink.
  • 12. American Art Collaborative Advisors Martin Doerr, Research Director at the Information Systems Laboratory and head of the Centre for Cultural Informatics of the Institute of Computer Science, FORTH Tim Finin, Professor of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County Craig Knoblock, Director of Data Integration, Information Sciences Institute, University of Southern California Robert Sanderson, Information Scientist at Stanford University Libraries Thorny Staples, Director of the Office of Research Information Services at the Smithsonian Institution
  • 13. Andrew W. Mellon Foundation Planning Grant American Art Collaborative Linked Open Data Initiative (AAC) Education Mission Statement Commitment Road Map
  • 14. Road Map over next 18 Months IMLS Leadership Grant Andrew W. Mellon Foundation Grant • 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
  • 15. • Develop several open source tools including a link curation tool and IIIF/CRM translator • Develop browse demonstration • Open access • Publish best practices and lessons learned
  • 16. Panel Discussion Why LOD •Everyone wants more meaningful content •Find new ways to share our information and keep audiences engaged •To augment our collection information by connecting to other museums and institutions •To better support research and improve access •Achieve seamless access across museums using LOD •Make our collections more discoverable •To tell fuller stories about our objects •Complementarity: e.g. archives about documents connecting to works of art •Explore cross domain connections •LOD makes our data more useable to developers
  • 17. Why Collaborative •Learning together •More comprehensive education •Building on diverse skills •Easier to engage and convince management •Grant Funding to train and produce •Create best practices
  • 18. Challenges and Uncertainties •Licensing •Mastering the CRM •Data inconsistencies •Implications of federated or hybrid models versus aggregation models •Learning curve and skill set •Accuracy of tools •Working with high end technology experts that are not art specialists •As new datasets come online, how to connect •URI identities and connecting to other resources like Getty Vocabularies that have their own URI
  • 19. •How to know what to connect to •How to make sure you are connecting to the right entity (person, place, etc.) •How to maintain the data •How to obtain metrics on impact of converting your data to LOD and see how visitors are using your data •Exploring what openness means •How to get dpedia to link back •How do you encourage people to link to your LOD Challenges and Uncertainties •How to retain the authority voice about the object
  • 20. Creative Commons license E.G. •Freeing content globally without restriction CC0 •Only with Attribution CCBY •Attribution and non commercial CCBY NC
  • 21. Why Federated Versus Aggregation Model •Better sustainability model: each responsible for updating and maintaining like websites •Vision of Tim Berners Lee (distributed data residing in a LOD Cloud) •Richness of data •Make data openly available for aggregators; include access nodes to other projects
  • 24. ISI’s Karma data integration tool http://isi.edu/integration/karma
  • 25. Best Practices Guidelines Eleanor and Diane W3C G AAC DfC Advisors ISI Emmanuelle SStead
  • 26. Introduction and Background includes what AAC identifies as the Initiative’s value added. E.g. leveraging expertise; being able to address tough technical questions Challenges including how to access data using a federated model Data preparation and mapping Including licensing, considerations in choosing an ontology, submitting data, CRM mapping, proofing, how accurate was Karma Linking and reconciliation issues Discrepancies in handling of dates, dimensions, etc; multiple URIs Creating apps (lessons learned browse demo) IIIF implementation Hosting Skills and timeframes Conclusions and recommendations Including issues the cultural heritage community will need to address and consider
  • 29. “Data that is in motion is much more preserveable than data on files” Cory Doctorow THANK YOU americanartcollaborative.org/