Overview and Framework for Data and Information Quality Research
Journal of Data and Information Quality (JDIQ)
TAPP'10 Proceedings of the 2nd conference on Theory and practice of provenance
The Foundations for Provenance on the Web
Foundations and Trends in Web Science
A provenance approach to assess the quality of geospatial data
Proceedings of the 27th Annual ACM Symposium on Applied Computing
A provenance-based approach to evaluate data quality in eScience
International Journal of Metadata, Semantics and Ontologies
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Data quality is crucial for operational efficiency and sound decision making. This paper focuses on believability, a major aspect of quality, measured along three dimensions: trustworthiness, reasonableness, and temporality. We ground our approach on provenance, i.e. the origin and subsequent processing history of data. We present our provenance model and our approach for computing believability based on provenance metadata. The approach is structured into three increasingly complex building blocks: (1) definition of metrics for assessing the believability of data sources, (2) definition of metrics for assessing the believability of data resulting from one process run and (3) assessment of believability based on all the sources and processing history of data. We illustrate our approach with a scenario based on Internet data. To our knowledge, this is the first work to develop a precise approach to measuring data believability and making explicit use of provenance-based measurements.