Data Drill-down

Data Drill-Down is an interactive data exploration technique that enables hierarchical navigation from aggregated to more granular levels of data to reveal underlying details within a dataset.

21

Publications

580

Citations

60

Authors

36

Institutions

Publications per year

2017–2026

5

Authors

60

  1. AP
    Aditya Parameswaran

    Stanford University, United States

    5 publications · 152 citations

    5

    h-index

  2. HG
    Héctor García-Molina

    Stanford University, United States

    4 publications · 102 citations

    4

    h-index

  3. MJ
    Manas Joglekar

    Stanford University, United States

    4 publications · 102 citations

    4

    h-index

  4. MB
    Mozammel Bin Motalab

    East West University, Bangladesh

    1 publications · 25 citations

    1

    h-index

  5. OT
    Olivier Teste

    Institut de Recherche en Informatique de Toulouse, France

    1 publications · 27 citations

    1

    h-index

1–5 of 60

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 2 publications · 41 citations

    2

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 1 publications · 31 citations

    1

    h-index

  3. IEEE Symposium on Information Visualization

    Conference · 1 publications · 10 citations

    1

    h-index

  4. Journal of Physics Conference Series

    1 publications · 32 citations

    1

    h-index

  5. The Cartographic Journal

    1 publications · 39 citations

    1

    h-index

1–5