Karma: A System for Easily Publishing Museum Data to the Linked Data Cloud
Pedro Szekely, University of Southern California, USA, Craig Knoblock, University of Southern California, USA, Jing Wan, Beijing University of Chemical Technology, China
Published paper: Karma: Tools for Mapping Collection Meta-Data to Linked Open Data
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 Karma, our system for mapping museum data to the Linked Data Cloud. We describe the capabilities in Karma to easily map the museum data to RDF according to an ontology of the user’s choice, to link the data to hub datasets such as DBpedia and other museum datasets, and for curating the data.