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Integrating PROV with DDI: Mechanisms of data discovery within the US Census Bureau

Presenter 1
Bill Block
Cornell University
Presenter 2
Warren Brown
Cornell University
Presenter 3
Jeremy Williams
Cornell University
Presenter 4
Lars Vilhuber
Cornell University
Presenter 5
Carl Lagoze
University of Michigan

Within the United States Census Bureau, datasets are often derived by complex methods that are not always well documented. This derivation process, or provenance, can be hard to understand for a researcher attempting to use or explore a given dataset. Without understanding the provenance of a dataset, it can be impossible establish whether it is appropriate to use for a given investigation, because its history remains a black box with no way to see inside. The infrastructure upon which the semantic web is built provides a means to label the relationships of social science datasets with logical meaning according to standardized ontologies and controlled vocabularies. This paper outlines the work of the Comprehensive Data Documentation and Access Repository (CED2AR) to integrate provenance metadata encoded according to the W3C PROV ontology with a DDI-based repository with the aim of making US Census data more discoverable and accessible.

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