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Managing information quality in e-science: the qurator workbench

Missier, Paolo, Embury, Suzanne M., Greenwood, Mark, Preece, Alun David and Jin, Binling 2007. Managing information quality in e-science: the qurator workbench. Presented at: ACM SIGMOD International Conference on Management of Data, Beijing, China, 11-14 June 2007. SIGMOD '07 Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data. New York: ACM, pp. 1150-1152. 10.1145/1247480.1247638

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Abstract

Data-intensive e-science applications often rely on third-party data found in public repositories, whose quality is largely unknown. Although scientists are aware that this uncertainty may lead to incorrect scientific conclusions, in the absence of a quantitative characterization of data quality properties they find it difficult to formulate precise data acceptability criteria. We present an Information Quality management workbench, called Qurator, that supports data experts in the specification of personal quality models, and lets them derive effective criteria for data acceptability. The demo of our working prototype will illustrate our approach on a real e-science workflow for a bioinformatics application.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: ACM
Last Modified: 04 Jun 2017 04:44
URI: http://orca-mwe.cf.ac.uk/id/eprint/43782

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