Abstract

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 and lessons learned in publishing the data from the Smithsonian American Art Museum (SAAM). We highlight complexities of the database-to-RDF mapping process, discuss our experience linking the SAAM dataset to hub datasets such as DBpedia and the Getty Vocabularies …

Date

September 22, 2025

Authors

Pedro Szekely, Craig A Knoblock, Fengyu Yang, Xuming Zhu, Eleanor E Fink, Rachel Allen, Georgina Goodlander

Conference

The Semantic Web: Semantics and Big Data: 10th International Conference, ESWC 2013, Montpellier, France, May 26-30, 2013. Proceedings 10

Pages

593-607

Publisher

Springer Berlin Heidelberg