Data Completeness

Data Completeness is a data quality dimension that refers to the extent to which all required data elements are present within a dataset, distinguishing itself by measuring the absence of missing values in relation to a defined set of expected attributes or records.

348

Publications

24.9K

Citations

1.6K

Authors

822

Institutions

Publications per year

2017–2026

182

Authors

1.6K

  1. SN
    Shawn N. Murphy

    Massachusetts General Hospital, United States

    5 publications · 333 citations

    5

    h-index

  2. CR
    Chalapati Rao

    The University of Queensland, Australia

    4 publications · 2.2K citations

    4

    h-index

  3. SB
    Stina B. Jonasson

    Skåne University Hospital, Sweden

    3 publications · 83 citations

    4

    h-index

  4. RL
    Rolf Lefering

    Witten/Herdecke University, Germany

    3 publications · 80 citations

    3

    h-index

  5. YG
    Yunjun Gao

    Zhejiang University, China

    3 publications · 131 citations

    3

    h-index

1–5 of 1.6K

Venues

  1. PubMed

    Repository · 9 publications · 2.1K citations

    10

    h-index

  2. Journal of the American Medical Informatics Association

    JAMIA · 6 publications · 256 citations

    6

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 5 publications · 263 citations

    6

    h-index

  4. PLoS ONE

    6 publications · 362 citations

    6

    h-index

  5. 3

    h-index

1–5