Explainable Visualization

Explainable Visualization is a type of visual representation that, as an academic concept, integrates transparent design principles and interpretability mechanisms to make the underlying data, analytical processes, and algorithmic reasoning of visual encodings explicitly understandable to human users.

45

Publications

2.1K

Citations

113

Authors

50

Institutions

Publications per year

2017–2026

33

Authors

113

  1. HP
    Haekyu Park

    Georgia Institute of Technology, United States

    1 publications · 329 citations

    2

    h-index

  2. DH
    Duen Horng Chau

    Georgia Institute of Technology, United States

    1 publications · 329 citations

    2

    h-index

  3. HQ
    Huamin Qu

    Hong Kong University of Science and Technology, Hong Kong SAR China

    1 publications · 51 citations

    2

    h-index

  4. ZJ
    Zijie J. Wang

    Georgia Institute of Technology, United States

    1 publications · 329 citations

    2

    h-index

  5. YZ
    Yang Zhang

    University of Sheffield, United Kingdom

    2 publications · 108 citations

    2

    h-index

1–5 of 113

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 158 citations

    5

    h-index

  2. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 3 publications · 509 citations

    4

    h-index

  3. RePEc: Research Papers in Economics

    Repository · 1 publications · 50 citations

    1

    h-index

  4. KOPS (University of Konstanz)

    Repository · 1 publications · 18 citations

    1

    h-index

  5. ACM Transactions on Interactive Intelligent Systems

    TIIS · 1 publications · 36 citations

    1

    h-index

1–5