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Publishing the Data of the Smithsonian American Art Museum to the Linked Data Cloud

Publishing the Data of the Smithsonian American Art Museum to the Linked Data Cloud <jats:p> Museums around the world have built databases with metadata about millions of objects, their history, the people who created them, and the entities they represent. This data is stored in proprietary databases and is not readily available for use. Recently, museums embraced the Semantic Web as a means to make this data available to the world, but the experience so far shows that publishing museum data to the linked data cloud is difficult: the databases are large and complex, the information is richly structured and varies from museum to museum, and it is difficult to link the data to other datasets. This paper describes the process of publishing the data of the Smithsonian American Art Museum (SAAM). We describe the database-to-RDF mapping process, discuss our experience linking the SAAM dataset to hub datasets such as DBpedia and the Getty Vocabularies, and present our experience in allowing SAAM personnel to review the information to verify that it meets the high standards of the Smithsonian. Using our tools, we helped SAAM publish high-quality linked data of their complete holdings: 41,000 objects and 8,000 artists. </jats:p> http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Humanities and Arts Computing Edinburgh University Press

Publishing the Data of the Smithsonian American Art Museum to the Linked Data Cloud

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References (14)

Publisher
Edinburgh University Press
Copyright
© Edinburgh University Press
Subject
Technology and Scaling; Historical Studies
ISSN
1753-8548
eISSN
1755-1706
DOI
10.3366/ijhac.2014.0104
Publisher site
See Article on Publisher Site

Abstract

<jats:p> Museums around the world have built databases with metadata about millions of objects, their history, the people who created them, and the entities they represent. This data is stored in proprietary databases and is not readily available for use. Recently, museums embraced the Semantic Web as a means to make this data available to the world, but the experience so far shows that publishing museum data to the linked data cloud is difficult: the databases are large and complex, the information is richly structured and varies from museum to museum, and it is difficult to link the data to other datasets. This paper describes the process of publishing the data of the Smithsonian American Art Museum (SAAM). We describe the database-to-RDF mapping process, discuss our experience linking the SAAM dataset to hub datasets such as DBpedia and the Getty Vocabularies, and present our experience in allowing SAAM personnel to review the information to verify that it meets the high standards of the Smithsonian. Using our tools, we helped SAAM publish high-quality linked data of their complete holdings: 41,000 objects and 8,000 artists. </jats:p>

Journal

International Journal of Humanities and Arts ComputingEdinburgh University Press

Published: Mar 1, 2014

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