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  7. Encoding Provenance Metadata for Social Science Datasets

Encoding Provenance Metadata for Social Science Datasets

File(s)
MTSR 2013 lagoze.pptx (797.67 KB)
Presentation of research at conference
Encoding Provenance for Social Science Data-final.pdf (660.17 KB)
PDF as submitted
Encoding Provenance for Social Science Data-final.docx (805.54 KB)
Word document
Permanent Link(s)
https://hdl.handle.net/1813/55327
Collections
Cornell University NCRN node
Author
Lagoze, Carl
Williams, Jeremy
Vilhuber, Lars
Abstract

Recording provenance is a key requirement for data-centric scholarship, allowing researchers to evaluate the integrity of source data sets and re- produce, 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.

Description
Submitted to Metadata and Semantics Research (MTSR 2013) conference.
Sponsorship
NSF Grant #1131848 (NCRN)
Date Issued
2013
Publisher
Springer
Keywords
metadata
•
provenance
•
DDI
Related DOI
https://doi.org/10.1007/978-3-319-03437-9_13
Previously Published as
Lagoze C., Willliams J., Vilhuber L. (2013) Encoding Provenance Metadata for Social Science Datasets. In: Garoufallou E., Greenberg J. (eds) Metadata and Semantics Research. MTSR 2013. Communications in Computer and Information Science, vol 390. Springer, Cham
Rights
Attribution-NonCommercial-ShareAlike 4.0 International
Rights URI
https://creativecommons.org/licenses/by-nc-sa/4.0/
Type
article

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