Access Restriction

Author Cheah, You-Wei ♦ Plale, Beth
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2014
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Data provenance ♦ Graph analysis ♦ Provenance quality ♦ Scientific workflow
Abstract Data provenance, a form of metadata describing the life cycle of a data product, is crucial in the sharing of research data. Research data, when shared over decades, requires recipients to make a determination of both use and trust. That is, can they use the data? More importantly, can they trust it? Knowing the data are of high quality is one factor to establishing fitness for use and trust. Provenance can be used to assert the quality of the data, but the quality of the provenance must be known as well. We propose a framework for assessing the quality of data provenance. We identify quality issues in data provenance, establish key quality dimensions, and define a framework of analysis. We apply the analysis framework to synthetic and real-world provenance.
ISSN 19361955
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-12-12
Publisher Place New York
e-ISSN 19361963
Journal Journal of Data and Information Quality (JDIQ)
Volume Number 5
Issue Number 3
Page Count 20
Starting Page 1
Ending Page 20

Open content in new tab

   Open content in new tab
Source: ACM Digital Library