Missing Data Queries

Missing Data Queries is a query management framework that systematically identifies, characterizes, and addresses incomplete or absent data elements within a dataset by formalizing the conditions under which data gaps affect analytical validity and prescribing actions for their resolution.

43

Publications

1.4K

Citations

114

Authors

67

Institutions

Publications per year

2017–2026

15

Authors

114

  1. MH
    Melanie Herschel

    University of Stuttgart, Germany

    4 publications · 149 citations

    4

    h-index

  2. LL
    Leonid Libkin

    University of Edinburgh, United Kingdom

    3 publications · 49 citations

    4

    h-index

  3. YG
    Yonis Gulzar

    King Faisal University, Saudi Arabia

    3 publications · 44 citations

    3

    h-index

  4. AA
    Ali A. Alwan

    International Islamic University Malaysia, Malaysia

    2 publications · 29 citations

    2

    h-index

  5. CL
    Christoph Lofi

    Delft University of Technology, Netherlands

    2 publications · 113 citations

    2

    h-index

1–5 of 114

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 6 publications · 231 citations

    6

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 5 publications · 169 citations

    5

    h-index

  3. IEEE Access

    2 publications · 27 citations

    2

    h-index

  4. Computer Systems: Science & Engineering

    1 publications · 13 citations

    1

    h-index

  5. Journal of the Egyptian Mathematical Society

    1 publications · 13 citations

    1

    h-index

1–5