High-dimensional Data Visualization

High-Dimensional Data Visualization is a subfield of data visualization that focuses on the graphical representation and interactive exploration of datasets with a large number of variables or dimensions, typically exceeding three, to facilitate the detection of patterns, clusters, and anomalies through dimensionality reduction, projection techniques, and multivariate encoding methods.

2.5K

Publications

234.6K

Citations

6K

Authors

1.6K

Institutions

Publications per year

2017–2026

613

Authors

6K

  1. DA
    Daniel A. Keim

    University of Konstanz, Germany

    56 publications · 4.3K citations

    31

    h-index

  2. HH
    Helwig Hauser

    University of Bergen, Norway

    22 publications · 2.3K citations

    21

    h-index

  3. KM
    Kwan‐Liu Ma

    University of California, Davis, United States

    25 publications · 1.4K citations

    19

    h-index

  4. MO
    Matthew O. Ward

    Worcester Polytechnic Institute, United States

    21 publications · 2.1K citations

    19

    h-index

  5. AT
    Alexandru Telea

    University of Groningen, Netherlands

    19 publications · 1.4K citations

    18

    h-index

1–5 of 6K

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 202 publications · 15.2K citations

    70

    h-index

  2. Computer Graphics Forum

    67 publications · 3.8K citations

    33

    h-index

  3. Journal of Computational and Graphical Statistics

    JCGS · 44 publications · 3.4K citations

    28

    h-index

  4. IEEE Computer Graphics and Applications

    38 publications · 2.6K citations

    24

    h-index

  5. Information Visualization

    40 publications · 2.2K citations

    24

    h-index

1–5