Data Quality Bias

Data Quality Bias is a systematic error in data quality assessment or measurement that arises from non-representative data sampling, flawed data collection procedures, or inherent limitations in data sources, leading to distorted or misleading conclusions about the true quality of data within a given context.

26

Publications

1K

Citations

74

Authors

30

Institutions

Publications per year

2017–2026

9

Authors

74

  1. FL
    Fay Lomax Cook

    Northwestern University, United States

    2 publications · 54 citations

    2

    h-index

  2. TR
    Tom R. Tyler

    New York University, United States

    2 publications · 54 citations

    2

    h-index

  3. EG
    Edward G. Goetz

    University of Minnesota, United States

    2 publications · 54 citations

    2

    h-index

  4. NG
    Niloufar Gharoon Dastjerdi

    University of Nevada, Reno, United States

    1 publications · 63 citations

    1

    h-index

  5. BC
    Bart Capéau

    KU Leuven, Belgium

    1 publications · 11 citations

    1

    h-index

1–5 of 74

Venues

  1. Journal of Marketing Research

    2 publications · 54 citations

    2

    h-index

  2. The Science of The Total Environment

    2 publications · 204 citations

    2

    h-index

  3. Landscape and Urban Planning

    1 publications · 27 citations

    1

    h-index

  4. Experimental and Clinical Psychopharmacology

    1 publications · 27 citations

    1

    h-index

  5. Oxford University Research Archive (ORA) (University of Oxford)

    Repository · 1 publications · 11 citations

    1

    h-index

1–5