Exploratory Data Visualization

Exploratory Data Visualization is a data visualization technique that enables analysts to iteratively examine and uncover underlying patterns, anomalies, and structures in data to inform hypothesis generation and further analysis.

400

Publications

63.5K

Citations

1.2K

Authors

504

Institutions

Publications per year

2017–2026

123

Authors

1.2K

  1. GA
    Gennady Andrienko

    Fraunhofer Institute for Intelligent Analysis and Information Systems, Germany

    6 publications · 353 citations

    6

    h-index

  2. NA
    Natalia Andrienko

    Fraunhofer Institute for Intelligent Analysis and Information Systems, Germany

    6 publications · 353 citations

    6

    h-index

  3. DF
    Danyel Fisher

    Microsoft (United States), United States

    5 publications · 532 citations

    5

    h-index

  4. ÇD
    Çağatay Demiralp

    Brown University, United States

    5 publications · 223 citations

    5

    h-index

  5. AM
    Alan M. MacEachren

    Pennsylvania State University, United States

    5 publications · 667 citations

    5

    h-index

1–5 of 1.2K

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 23 publications · 2K citations

    20

    h-index

  2. Computer Graphics Forum

    8 publications · 319 citations

    8

    h-index

  3. Nucleic Acids Research

    7 publications · 5K citations

    7

    h-index

  4. arXiv (Cornell University)

    Repository · 7 publications · 180 citations

    7

    h-index

  5. Information Visualization

    5 publications · 180 citations

    5

    h-index

1–5