The notion of data and its quality dimensions
Information Processing & ManagementPublished 1 January 1994
Chris Fox, Anany Levitin, Thomas C. Redman
Citations256
SJR quartileQ1
SJR score2.06
SNIP2.91
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TL;DR
The most important dimensions of data quality: accuracy, completeness, consistency and currentness are defined and several related dimensions are discussed and defined and discussed in detail.
Abstract
The rapid proliferation of computer-based information systems is increasing the importance of data quality to both system makers and users. However, there is neither an established framework nor common terminology for investigating data quality. There is not even agreement on what the term "data" means. We lay a foundation for the study of data quality in this paper. In the first part of the paper we discuss five approaches to defining "data" in the literature. We then propose an approach especially conducive to discussing data quality. In the second part of the paper we discuss the most important dimensions of data quality: accuracy, completeness, consistency and currentness. We define these four and several related dimensions and discuss them in detail. We close the paper by outlining several areas for further research on data quality.
Keywords
Computer ScienceDecision Sciences
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