Encoding Provenance Metadata for Social Science Datasets

  • Carl Lagoze
  • Jeremy Willliams
  • Lars Vilhuber
Part of the Communications in Computer and Information Science book series (CCIS, volume 390)

Abstract

Recording provenance is a key requirement for data-centric scholarship, allowing researchers to evaluate the integrity of source data sets and reproduce, and thereby, validate results. Provenance has become even more critical in the web environment in which data from distributed sources and of varying integrity can be combined and derived. Recent work by the W3C on the PROV model provides the foundation for semantically-rich, interoperable, and web-compatible provenance metadata. We apply that model to complex, but characteristic, provenance examples of social science data, describe scenarios that make scholarly use of those provenance descriptions, and propose a manner for encoding this provenance metadata within the widely-used DDI metadata standard.

Keywords

Metadata Provenance DDI eSocial Science 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Carl Lagoze
    • 1
  • Jeremy Willliams
    • 2
  • Lars Vilhuber
    • 3
  1. 1.School of InformationUniversity of MichiganAnn ArborUSA
  2. 2.Cornell Institute for Social and Economic ResearchCornell UniversityIthacaUSA
  3. 3.School of Industrial and Labor RelationsCornell UniversityIthacaUSA

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