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The Blossoming of the Semantic Web:
Linked Open Data and the American Art Collaborative

Diana Folsom

Eleanor Fink:

Head of Collection Digitization

Art and Technology Advisor and Project
Coordinator

Thomas Gilcrease Institute of American History
and Culture (Gilcrease Museum)

Information Sciences Institute, USC

Rachel Allen:

Pedro Szekely

Deputy Director

Project Leader

Smithsonian American Art Museum

Information Sciences Institute, USC

Shane Richey
Digital Media Manager
Crystal Bridges Museum of American Art
AmericanArtCollaborative.org
LINKED OPEN DATA LANDSDCAPE
Eleanor E. Fink, Art and Technology Consultant
Linked Open Data
A method of publishing structured data so that it can be
interlinked and become more useful
Uses a markup language called RDF that allows the
relationship between subject, predicate, and object to be
tagged explicitly so that when you are searching using
Linked Open Data you don’t get the “noise” or unrelated
information you get with a Google search
facts:
<subject> <predicate> <object>
using W3C standards (RDF)

Linked Data
links between facts from different
databases
like links between Web pages

University of Southern California

Pedro Szekely and Craig Knoblock
Linked Open Data tears down data silos
LOD CLOUD
Window to Universe of Knowledge
Linked Open Data
•
•

tears down data silos
provides seamless access across
museums and world of knowledge (articles,
objects in other museums ,obituaries, Wikipedia,
New York Times, etc.)
• provides rich content that supports K-12
education around the country
Linked Open Data

•

deepens experience of audiences and reaches
new audiences
• can engage audiences in research and change
how museums connect with people
• can lead to innovative funding through new
applications
The Blossoming of the Semantic Web
The Blossoming of the Semantic Web
The Blossoming of the Semantic Web
The Blossoming of the Semantic Web
The Blossoming of the Semantic Web
American Art Collaborative
American Art Collaborative
connections across websites and world of knowledge
Smithsonian American Art Museum
and USC Information Sciences
Institute
How We Did It
Rachel Allen, Deputy Director, SAAM and
Eleanor E. Fink, Art and Technology Consultant
The American Art Museum
A National Mandate and a
Populist Approach
American Art’s Technology Goals






Be a crossroads for American art
Lead in use of new media
Experiment with technology
Expand outreach
Attract the born-digital generation
Benefits of Linked Open Data







Make our collections data more discoverable
Allow for sophisticated queries about data
Create connections with other museums
Create connections with other resources
Create connections with dispersed content on
social media
Help us better adapt to the changing web
Our Team Questions about LOD





Will it take too much time to prepare our data?
How does LOD differ from a Google search?
Is it foolish to do before standards are in place?
What if people do inappropriate things with our
data?
 Will it be worth the time and effort in the end?
 How do we handle our non-public data?
Five Phases to Linked Open Data






Prepare the data
Determine the ontology
Map the data to RDF
Link to hub datasets
Publish the data.
Linking the American Art Museum to the Cloud
The Process: SAAM Ontology
Linking the American Art Museum to the Cloud
The Process
Mapping the Data to RDF (Resource Description Framework)
• Used KARMA tool to model the data (http://www.isi.edu/integration/karma/)
Ontology: CRM
Ontology: EDM2





distinguishing between a 'provided item' (painting, book) and its
digital representations
distinguishing between an item and the metadata record
describing it
allowing the ingestion of multiple records for the same item,
which may contain contradictory statements about it
EDM re-uses elements coming from already-established
vocabularies, such as Dublin Core, OAI-ORE, SKOS and CIDOC-CRM
Information Sciences Institute

Early work with DARPA and creation of
Internet
Current work also with private sector, NSF,
government, military, museums etc. E.g.
R & D, cyber security, internet protocols, Linked
Open Data, etc.
ISI Research Environment is Unique in Academia:
5-10 Year Full Research-To-Transition Cycle
BASIC
RESEARCH

PhD
theses
Graduate
projects

CROSS-DISCIPLINARY
RESEARCH & INTEGRATION

DEPLOYMENT &
COMMERCIALIZATION

ISI Startups
CrossDisciplinary
Multi-Institutional
Collaborations

Collabs
w/ companies
& customers

Academic and
Curriculum
Development,
Teaching

Broad Range of
Expertise and
Interests

Faster and
Comprehensive
Delivery of Basic
Research Products

NSF, AFOSR, NIH, NRL

DARPA, NSF, NIH, DTO

SOCOM, DARPA, AFRL
ISI’s Expertise
http://isi.edu/integration/karma
KARMA
A Data Integration Tool that eliminates data silos
KARMA






KARMA, open source, semi-automated,
interactive, data integration tool that makes LOD
conversion easy
Initially developed 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)
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 94%
matching score)
Staff can interact with tool to make
adjustments
KARMA
Increases data accuracy
Scales to large databases
Keeps Linked Data up-to-date
Karma’s Current Audience
Intelligence
Science
Cultural Heritage

Entertainment
…anyone who needs to
tear down data silos
The Blossoming of the Semantic Web
Link Curation

University of Southern California

Pedro Szekely and Craig Knoblock
PROCESS: LINKING EXTERNALLY
Completed:
• DBPedia - 2,194
• New York Times – 70
• Getty Union List of Artist Names - 2,110 Rijksmuseum
dataset – 551
• In the Future:
• Places
• Concepts
• Other museum datasets
• Social media content
Match Precision Linking Museum Data

DBPedia
New York Times

University of Southern California

2,194
70

Getty ULAN®
Rijksmuseum
Geonames

2,110
551
3,068

Pedro Szekely and Craig Knoblock
University of Southern California

Pedro Szekely and Craig Knoblock
The Blossoming of the Semantic Web
The Blossoming of the Semantic Web
Immediate Next Steps





Verify geographic place links
Add other additional links
Develop an ongoing management plan
Take over hosting of the OWLIM database



Publish and announce the SPARQL endpoint
Future Applications







Improve artist representation on Wikipedia
Embed LOD into our website
Tag and link museum social media content
Expand our use of LOD to enhance research
Relationship finder application for curating stories
Encourage development of museum applications
Multimedia Stories
ESWC 2013
Extended Semantic Web Conference
Benefits and Opportunities
Linked Open Data can:
Create connections across diverse systems,
(locally, regionally, around the globe)
 Provide new ways to conduct business, find
information, develop applications
 Lead to discovery of new research and new
ideas across disciplines

Next Steps
The Semantic Web needs more cultural information
Become a part of the LOD cloud and help us build a
critical mass of linked cultural data!
Together we can
Seek funding for data conversion and ongoing
maintenance
Provide tools like KARMA
Develop training and education about linked open data
Build a collaborative and supportive network of
practitioners
Join Us
Thank You
Questions and Discussion

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The Blossoming of the Semantic Web

  • 1. Brought to you by Live streaming and video recordings made possible by
  • 2. The Blossoming of the Semantic Web: Linked Open Data and the American Art Collaborative Diana Folsom Eleanor Fink: Head of Collection Digitization Art and Technology Advisor and Project Coordinator Thomas Gilcrease Institute of American History and Culture (Gilcrease Museum) Information Sciences Institute, USC Rachel Allen: Pedro Szekely Deputy Director Project Leader Smithsonian American Art Museum Information Sciences Institute, USC Shane Richey Digital Media Manager Crystal Bridges Museum of American Art
  • 4. LINKED OPEN DATA LANDSDCAPE Eleanor E. Fink, Art and Technology Consultant
  • 5. Linked Open Data A method of publishing structured data so that it can be interlinked and become more useful Uses a markup language called RDF that allows the relationship between subject, predicate, and object to be tagged explicitly so that when you are searching using Linked Open Data you don’t get the “noise” or unrelated information you get with a Google search
  • 6. facts: <subject> <predicate> <object> using W3C standards (RDF) Linked Data links between facts from different databases like links between Web pages University of Southern California Pedro Szekely and Craig Knoblock
  • 7. Linked Open Data tears down data silos
  • 8. LOD CLOUD Window to Universe of Knowledge
  • 9. Linked Open Data • • tears down data silos provides seamless access across museums and world of knowledge (articles, objects in other museums ,obituaries, Wikipedia, New York Times, etc.) • provides rich content that supports K-12 education around the country
  • 10. Linked Open Data • deepens experience of audiences and reaches new audiences • can engage audiences in research and change how museums connect with people • can lead to innovative funding through new applications
  • 17. American Art Collaborative connections across websites and world of knowledge
  • 18. Smithsonian American Art Museum and USC Information Sciences Institute How We Did It Rachel Allen, Deputy Director, SAAM and Eleanor E. Fink, Art and Technology Consultant
  • 20. A National Mandate and a Populist Approach
  • 21. American Art’s Technology Goals      Be a crossroads for American art Lead in use of new media Experiment with technology Expand outreach Attract the born-digital generation
  • 22. Benefits of Linked Open Data       Make our collections data more discoverable Allow for sophisticated queries about data Create connections with other museums Create connections with other resources Create connections with dispersed content on social media Help us better adapt to the changing web
  • 23. Our Team Questions about LOD     Will it take too much time to prepare our data? How does LOD differ from a Google search? Is it foolish to do before standards are in place? What if people do inappropriate things with our data?  Will it be worth the time and effort in the end?  How do we handle our non-public data?
  • 24. Five Phases to Linked Open Data      Prepare the data Determine the ontology Map the data to RDF Link to hub datasets Publish the data.
  • 25. Linking the American Art Museum to the Cloud The Process: SAAM Ontology
  • 26. Linking the American Art Museum to the Cloud The Process Mapping the Data to RDF (Resource Description Framework) • Used KARMA tool to model the data (http://www.isi.edu/integration/karma/)
  • 28. Ontology: EDM2     distinguishing between a 'provided item' (painting, book) and its digital representations distinguishing between an item and the metadata record describing it allowing the ingestion of multiple records for the same item, which may contain contradictory statements about it EDM re-uses elements coming from already-established vocabularies, such as Dublin Core, OAI-ORE, SKOS and CIDOC-CRM
  • 29. Information Sciences Institute Early work with DARPA and creation of Internet Current work also with private sector, NSF, government, military, museums etc. E.g. R & D, cyber security, internet protocols, Linked Open Data, etc.
  • 30. ISI Research Environment is Unique in Academia: 5-10 Year Full Research-To-Transition Cycle BASIC RESEARCH PhD theses Graduate projects CROSS-DISCIPLINARY RESEARCH & INTEGRATION DEPLOYMENT & COMMERCIALIZATION ISI Startups CrossDisciplinary Multi-Institutional Collaborations Collabs w/ companies & customers Academic and Curriculum Development, Teaching Broad Range of Expertise and Interests Faster and Comprehensive Delivery of Basic Research Products NSF, AFOSR, NIH, NRL DARPA, NSF, NIH, DTO SOCOM, DARPA, AFRL
  • 32. KARMA A Data Integration Tool that eliminates data silos
  • 33. KARMA    KARMA, open source, semi-automated, interactive, data integration tool that makes LOD conversion easy Initially developed 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)
  • 34. 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 94% matching score) Staff can interact with tool to make adjustments
  • 35. KARMA Increases data accuracy Scales to large databases Keeps Linked Data up-to-date
  • 36. Karma’s Current Audience Intelligence Science Cultural Heritage Entertainment …anyone who needs to tear down data silos
  • 38. Link Curation University of Southern California Pedro Szekely and Craig Knoblock
  • 39. PROCESS: LINKING EXTERNALLY Completed: • DBPedia - 2,194 • New York Times – 70 • Getty Union List of Artist Names - 2,110 Rijksmuseum dataset – 551 • In the Future: • Places • Concepts • Other museum datasets • Social media content
  • 40. Match Precision Linking Museum Data DBPedia New York Times University of Southern California 2,194 70 Getty ULAN® Rijksmuseum Geonames 2,110 551 3,068 Pedro Szekely and Craig Knoblock
  • 41. University of Southern California Pedro Szekely and Craig Knoblock
  • 44. Immediate Next Steps     Verify geographic place links Add other additional links Develop an ongoing management plan Take over hosting of the OWLIM database  Publish and announce the SPARQL endpoint
  • 45. Future Applications       Improve artist representation on Wikipedia Embed LOD into our website Tag and link museum social media content Expand our use of LOD to enhance research Relationship finder application for curating stories Encourage development of museum applications
  • 47. ESWC 2013 Extended Semantic Web Conference
  • 48. Benefits and Opportunities Linked Open Data can: Create connections across diverse systems, (locally, regionally, around the globe)  Provide new ways to conduct business, find information, develop applications  Lead to discovery of new research and new ideas across disciplines 
  • 49. Next Steps The Semantic Web needs more cultural information Become a part of the LOD cloud and help us build a critical mass of linked cultural data! Together we can Seek funding for data conversion and ongoing maintenance Provide tools like KARMA Develop training and education about linked open data Build a collaborative and supportive network of practitioners

Editor's Notes

  1. An augmented version of Europeana Data Model v.2 for overall framework; SKOS for classification of artworks, artist and place names; Dublin Core for tombstone data; RDA Group 2 Elements for biographical information; schema.org for geographical data.