Data Quality Dimensions

Data quality attributes; Data quality criteria; Data quality measurement

Data quality (DQ) is usually understood as a multi-dimensional concept. The dimensions represent the views, criteria, or measurement attributes for data quality problems that can be assessed, interpreted, and possibly improved individually. By assigning scores to these dimensions, the overall data quality can be determined as an aggregated value of individual dimensions relevant in the given application context.

Since the mid-1990s data quality issues have been addressed by systematic research studies. In this context, relevant dimensions of data quality have also been investigated. One of the first empirical studies by Wang and Strong [6] has identified 15 relevant dimensions out of 179 gathered criteria. This list was later supplemented by other researchers. Initially, there were proposed divergent definitions of the same dimensions, mostly due to different views, e.g.,...

Authors and Affiliations

1. Technische Universität Ilmenau, Ilmenau, Germany

   Kai-Uwe Sattler

Corresponding author

Correspondence to Kai-Uwe Sattler .

Editors and Affiliations

1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

   Ling Liu

2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

   M. Tamer Özsu

1. Information Systems, Hasso-Plattner-Institute, Potsdam, Germany

   Felix Naumann

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