20 Guimaraes, Yoon & Aiken
Copyright Idea Group Inc.
Copyright Idea Group Inc.
Copyright Idea Group Inc.
Copyright Idea Group Inc.
Chapter II
Using a Metadata
Framework To Improve
Data Resources Quality
Tor Guimaraes
Tennessee Technological University, USA
Youngohc Yoon
University of Maryland, Baltimore, USA
Peter Aiken
Defense Information Systems Agency, USA
The importance of properly managing the quality of organizational data
resources is widely recognized. A metadata framework is presented as the critical
tool in addressing the necessary requirements to ensure data quality. This is
particularly useful in increasingly encountered complex situations where data usage
crosses system boundaries. 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. Each of these, in turn, is described in
terms of specific data quality attributes.
The importance of a company-wide framework for managing data resources
has been recognized (Gunter, 2001; Sawhney, 2001; Stewart, 2001). It is considered
a major component of information resources management (Guimaraes, 1988). The
This chapter appears in the book, Advanced Topics in Information Resources Management by Mehdi
Khosrow-Pour.
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