Background Data Quality Assessment

Background Data Quality Assessment is a scholarly evaluation framework that systematically identifies, analyzes, and verifies the accuracy, completeness, consistency, and reliability of background data within a given dataset or information system to ensure its suitability for academic research and analytical applications.

23

Publications

3.8K

Citations

87

Authors

41

Institutions

Publications per year

2017–2026

3

Authors

87

  1. MB
    Michael Ball

    University of Reading, United Kingdom

    2 publications · 88 citations

    2

    h-index

  2. MW
    Maurits W. van Tulder

    Amsterdam UMC Location Vrije Universiteit Amsterdam, Netherlands

    2 publications · 2.4K citations

    2

    h-index

  3. CB
    Claire Bombardier

    University of Toronto, Canada

    2 publications · 2.4K citations

    2

    h-index

  4. OP
    Olaf Päpke

    Berufsgenossenschaft für Gesundheitsdienst und Wohlfahrtspflege, Germany

    2 publications · 88 citations

    2

    h-index

  5. AD
    Andrea D Furlan

    University of Toronto, Canada

    2 publications · 2.4K citations

    2

    h-index

1–5 of 87

Venues

  1. Spine

    4 publications · 2.5K citations

    4

    h-index

  2. Chemosphere

    2 publications · 88 citations

    2

    h-index

  3. Journal of Hazardous Materials

    1 publications · 11 citations

    1

    h-index

  4. Diversity and Distributions

    1 publications · 36 citations

    1

    h-index

  5. 1

    h-index

1–5