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Forget Dimensions: Define Your Information Quality Using Quality View Patterns

Lookup NU author(s): Professor Paolo MissierORCiD

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Abstract

© 2014, Springer International Publishing Switzerland.When creating software components that aim to alleviate information quality problems, it is necessary to elicit the requirements that the problem holders have, as well as the details of the existing technical infrastructure that will form the basis of the solution. In the literature, standard sets of IQ dimensions have been proposed as a means of initiating and structuring the information gathering and design processes involved. Over the past decade, we have been involved in several projects to develop IQ assessment components. In the earlier projects, we tried hard to make use of the standard IQ dimensions in this way, but found that we derived little benefit from this approach. In some cases, the IQ problem we were focussed on could not be assigned cleanly to one dimension or another. In others, the dimension was clear, but we found that that knowledge saved us very little of the work we had to do when the dimension was not identified up front. However, IQ problems are typically very challenging, and some sort of guiding principles are needed. In this paper, we propose our earlier notion of the Quality View (QV) as an alternative (or additional) technique to IQ dimensions for developing IQ management components. We reflect on our experiences in using QVs in three quite different IQ-related projects, and show how our initial basic pattern turned out to be a good starting point for the information gathering and design tasks involved, replacing IQ dimensions in the role originally envisaged for them.


Publication metadata

Author(s): Embury SM, Missier P

Publication type: Book Chapter

Publication status: Published

Book Title: Synthese Library

Year: 2014

Volume: 358

Pages: 25-41

Online publication date: 15/07/2014

Acceptance date: 01/01/1900

Series Title: Part of the Synthese Library book series

Publisher: Springer Science and Business Media B.V.

URL: https://doi.org/10.1007/978-3-319-07121-3_3

DOI: 10.1007/978-3-319-07121-3_3

Library holdings: Search Newcastle University Library for this item

ISBN: 9783319071206


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