Data Quality Dimensions

Data Quality Dimensions is a theoretical construct that categorizes the fundamental attributes used to assess the quality of data, distinguishing itself by specifying measurable aspects such as accuracy, completeness, consistency, timeliness, and other criteria that collectively define the fitness of data for its intended use.

261

Publications

25.6K

Citations

761

Authors

371

Institutions

Publications per year

2017–2026

114

Authors

761

  1. CB
    Carlo Batini

    University of Milano-Bicocca, Italy

    7 publications · 406 citations

    7

    h-index

  2. BH
    Bernd Heinrich

    University of Vermont, United States

    6 publications · 272 citations

    6

    h-index

  3. MK
    Mathias Klier

    University of Regensburg, Germany

    5 publications · 243 citations

    5

    h-index

  4. RS
    Ron S. Kenett

    University of Turin, Italy

    4 publications · 175 citations

    4

    h-index

  5. SS
    Samira Si-Saïd Cherfi

    Centre d'études et de recherche en informatique et communications, France

    4 publications · 228 citations

    4

    h-index

1–5 of 761

Venues

  1. Journal of Data and Information Quality

    JDIQ · 6 publications · 376 citations

    6

    h-index

  2. Decision Support Systems

    4 publications · 388 citations

    4

    h-index

  3. Journal of the Association for Information Systems

    JAIS · 4 publications · 78 citations

    4

    h-index

  4. ICIQ

    4 publications · 89 citations

    4

    h-index

  5. IQ

    4 publications · 152 citations

    4

    h-index

1–5