Collaborative Data Exploration

Collaborative Data Exploration is a scholarly framework that enables multiple users to simultaneously engage in the interactive analysis and interpretation of complex datasets within shared digital environments, distinguished by its integration of asynchronous collaboration, co-located collaborative visualization, and immersive data exploration techniques to support collective insight generation.

126

Publications

10.3K

Citations

651

Authors

262

Institutions

Publications per year

2017–2026

59

Authors

651

  1. OS
    Orit Shaer

    Wellesley College, United States

    4 publications · 198 citations

    4

    h-index

  2. JL
    Jason Leigh

    University of Illinois Chicago, United States

    3 publications · 73 citations

    3

    h-index

  3. SC
    Sheelagh Carpendale

    University of Calgary, Canada

    3 publications · 104 citations

    3

    h-index

  4. PI
    Petra Isenberg

    Institut national de recherche en sciences et technologies du numérique, France

    3 publications · 206 citations

    3

    h-index

  5. AN
    Atul Nayak

    Scripps Institution of Oceanography, United States

    2 publications · 34 citations

    2

    h-index

1–5 of 651

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 8 publications · 480 citations

    8

    h-index

  2. IEEE Computer Graphics and Applications

    4 publications · 237 citations

    4

    h-index

  3. BMC Bioinformatics

    3 publications · 246 citations

    3

    h-index

  4. Proceedings of the ACM on Human-Computer Interaction

    PACMHCI · 3 publications · 208 citations

    3

    h-index

  5. 3

    h-index

1–5