Data Exploration

Data Exploration is a systematic analytical process within the domain of interactive data analysis that involves the iterative examination and visualization of datasets to identify patterns, anomalies, and underlying structures without predefined hypotheses.

1.1K

Publications

100.5K

Citations

3.9K

Authors

1.3K

Institutions

Publications per year

2017–2026

441

Authors

3.9K

  1. AP
    Aditya Parameswaran

    Stanford University, United States

    11 publications · 369 citations

    11

    h-index

  2. KM
    Kwan‐Liu Ma

    University of California, Davis, United States

    10 publications · 375 citations

    10

    h-index

  3. BS
    Ben Shneiderman

    University of Maryland, College Park, United States

    9 publications · 626 citations

    9

    h-index

  4. DA
    Daniel A. Keim

    University of Konstanz, Germany

    8 publications · 2.8K citations

    8

    h-index

  5. BL
    Bongshin Lee

    Microsoft (United States), United States

    8 publications · 566 citations

    8

    h-index

1–5 of 3.9K

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 72 publications · 7.6K citations

    41

    h-index

  2. arXiv (Cornell University)

    Repository · 26 publications · 1.1K citations

    19

    h-index

  3. BMC Bioinformatics

    20 publications · 1.7K citations

    17

    h-index

  4. Bioinformatics

    21 publications · 3.1K citations

    16

    h-index

  5. Proceedings of the VLDB Endowment

    PVLDB · 17 publications · 525 citations

    13

    h-index

1–5