By Mehdi Khosrowpour
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Additional resources for Advanced Topics in Information Resources Management Series, Vol. 1
It is considered a major component of information resources management (Guimaraes, 1988). The Copyright © 2002, Idea Group Publishing. Using a Metadata Framework To Improve Data Resources Quality 21 complexity of data resources management is increasing as computer applications become more accessible to mobile users (Nesdore, 2001) and organizations attempt to extract more value from their data (Webb, 1999). As the volume, importance, and complexity of data management increases, many organizations are discovering that imperfect data in information systems negatively affects their business operations and can be extremely costly (Brown, 2001).
Letter to editor in response to Inc. Technology #3, Sep. 15, 1999, special issue on Knowledge Management]. htm. Malhotra, Y. (in press). ” In Srikantaiah, K. and Koenig, M. E. D. ), Knowledge Management for the Information Professional, Information Today, Medford, NJ. Malhotra, Y. and Kirsch, L. (1996). Personal construct analysis of self-control in IS adoption: Empirical evidence from comparative case studies of IS users and IS champions. , May 5-8, 105-114. Manville, B. and Foote, N. (1996).
The basic concept of metadata quality as a foundation for data quality engineering is discussed, as well as an extended data life cycle model consisting of eight phases: metadata creation, metadata structuring, metadata refinement, data creation, data utilization, data assessment, data refinement, and data manipulation. This extended model will enable further development of life cycle phase-specific data quality engineering methods. The paper also expands the concept of applicable data quality dimensions, presenting data quality as a function of four distinct components: data value quality, data representation quality, data model quality, and data architecture quality.
Advanced Topics in Information Resources Management Series, Vol. 1 by Mehdi Khosrowpour