Managing information quality in e-science: a case study in proteomics

Authors:
Paolo Missier;Alun Preece;Suzanne Embury;Binling Jin;Mark Greenwood;David Stead;Al Brown
Affiliations:
School of Computer Science, University of Manchester, Manchester, UK;Computing Science, University of Aberdeen, Aberdeen, UK;School of Computer Science, University of Manchester, Manchester, UK;Computing Science, University of Aberdeen, Aberdeen, UK;School of Computer Science, University of Manchester, Manchester, UK;Molecular and Cell Biology, University of Aberdeen, Aberdeen, UK;Molecular and Cell Biology, University of Aberdeen, Aberdeen, UK
Venue:
ER'05 Proceedings of the 24th international conference on Perspectives in Conceptual Modeling
Year:
2005

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Abstract

We describe a new approach to managing information quality (IQ) in an e-Science context, by allowing scientists to define the quality characteristics that are of importance in their particular domain. These preferences are specified and classified in relation to a formal IQ ontology, intended to support the discovery and reuse of scientists' quality descriptors and metrics. In this paper, we present a motivating scenario from the biological sub-domain of proteomics, and use it to illustrate how the generic quality model we have developed can be expanded incrementally without making unreasonable demands on the domain expert who maintains it.