Data Quality Uncertainty

Data Quality Uncertainty is a data quality construct that characterizes the degree of doubt or imprecision associated with the correctness, completeness, and reliability of data values within a given context.

29

Publications

2.7K

Citations

100

Authors

74

Institutions

Publications per year

2017–2026

9

Authors

100

  1. RD
    R. Daren Harmel

    Grassland, Soil and Water Research Laboratory, United States

    2 publications · 496 citations

    2

    h-index

  2. SS
    Stein Sandven

    Nansen Environmental and Remote Sensing Center

    2 publications · 217 citations

    2

    h-index

  3. MC
    Menzie Chinn

    University of Wisconsin–Madison, United States

    2 publications · 34 citations

    2

    h-index

  4. SB
    Sophie Bontemps

    UCLouvain, Belgium

    2 publications · 217 citations

    2

    h-index

  5. MR
    Maximilian Reuter

    University of Bremen, Germany

    2 publications · 217 citations

    2

    h-index

1–5 of 100

Venues

  1. Political Studies Review

    PSR · 1 publications · 11 citations

    1

    h-index

  2. European Economic Review

    1 publications · 31 citations

    1

    h-index

  3. The Analyst

    1 publications · 174 citations

    1

    h-index

  4. Journal of Environmental and Engineering Geophysics

    JEEG · 1 publications · 111 citations

    1

    h-index

  5. 1

    h-index

1–5