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OpenGLAM: LOD and American Art
1. Linking the American Art Museum to the Cloud
What is Linked Open Data? (Bear with me…)
Data published by existing internet protocols that use a URI (Unique Resource Indicator) as the
primary discoverable entity for a resource (e.g. person, object, web page, etc.)
THE FIVE STARS OF LOD (Tim Berners Lee):
★ make your stuff available on the web (whatever format) under an open license
★★ make it available as structured data (e.g., Excel instead of image scan of a table)
★★★ use non-proprietary formats (e.g., CSV instead of Excel)
★★★★ use URIs to identify things, so that people can point at your stuff
★★★★★ link your data to other data to provide context
2. Linking the American Art Museum to the Cloud
What is Linked Open Data good for?
For the American Art Museum, Linked Open Data will:
• Make our collections data more discoverable on the web
• Allow for more sophisticated queries about our collections
• Create connections with other museums
• Create connections with other non-museum resources
• Create connections with our dispersed content on social media
• Help us better adapt to the changing web
3. Linking the American Art Museum to the Cloud
Current State of (most) Cultural Heritage Data: Info from web pages
6. Linking the American Art Museum to the Cloud
Examples
Europeana
• Digitized collections of museums, libraries, archives and galleries across Europe.
• Open metadata on 20 million texts, images, videos and sounds
• A subset of 2.4 millions objects from 8 direct Europeana providers encompassing over 200
cultural institutions from 15 countries is served according to the Linked Data recipes.
• Virtual exhibitions showcase some of the content available.
7. Linking the American Art Museum to the Cloud
Examples
Pelagios
• Stands for 'Pelagios: Enable Linked Ancient Geodata In Open Systems’
• Aim is to help introduce Linked Open Data into online resources that refer to places in the
Ancient World.
• Allows you to find content related to a specific place
8. Linking the American Art Museum to the Cloud
Getting Started
Our Initial Questions
• Will it take a lot of time and resources to prepare our data?
• How does LOD differ from what a Google search can do?
• Is it foolish to be doing this 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 all of the non-public data that we have?
The Project
• Working with the Information Sciences Institute (ISI) and Department of Computer Science at
the University of Southern California.
• Goal: Publish 5-star Linked Open Data of our complete collections data.
• Project Phases: Prepare the data, Create an ontology, map the data to RDF, link the data to
hub datasets, publish the data.
9. Linking the American Art Museum to the Cloud
The Process
Preparing the data
• Collections data is stored in TMS
• Publish only the data that is already visible on our website
• Use an existing output report from TMS
• Several fields needed to be interpreted first
Designing the Ontology
• We built our ontology around existing ontologies
• Europeana Data Model v.2
• SKOS
• Dublin Core
• RDA Group 2 Elements
• schema.org
11. 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
12. Linking the American Art Museum to the Cloud
The Process
Linking the Data to External Data
• Verify matches before publishing
13. Linking the American Art Museum to the Cloud
The Process
Linking the Data to External Data (cont…)
• Have already linked artists to:
• DBPedia - 2,194
• New York Times - 70
• Additionally, can link artists to:
• Getty Union List of Artist Names - 2,110 (ULAN is not yet published as LOD, but will be)
• Rijksmuseum dataset – 551 (links are not yet verified)
• In the works:
• Linking places
• Linking concepts
• Linking to datasets from other museums
• Linking to social media content
Publishing
• Plan to publish complete dataset under a CC0 license
14. Linking the American Art Museum to the Cloud
Conclusions
• Able to convert data for entire collection
• Using KARMA to model the data and verify links reduced time and resources
• LOD eliminates the “noise” of a Google search
What’s next?
• Embed LOD on our website
• Improve representation of artists on Wikipedia
• Create an ongoing maintenance plan
• Tag object- and person-related museum content on social sites
• Investigate mapping and linking an artwork’s subject
• Expand the LOD in ways that will enhance research
• Create a tool that allows users to “curate stories”:
• http://prezi.com/htrvh2jrcsio/curating-stories-with-linked-open-data/
• Encourage others to build applications with our data