Mixed-data Visualization

Mixed-Data Visualization is a multivariate data visualization method that integrates and graphically represents heterogeneous data types—such as categorical, numerical, textual, and ordinal variables—within a unified visual framework to reveal complex inter-variable relationships across disparate data modalities.

8

Publications

376

Citations

24

Authors

11

Institutions

Publications per year

2017–2026

5

Authors

24

  1. LE
    Lennart E. Nacke

    University of Waterloo, Canada

    1 publications · 27 citations

    1

    h-index

  2. IH
    Ibrahim H. Yeter

    Nanyang Technological University, Singapore

    1 publications · 35 citations

    1

    h-index

  3. RC
    Rahul C. Basole

    Georgia Institute of Technology, United States

    1 publications · 17 citations

    1

    h-index

  4. VG
    V.V. Gubarev

    Novosibirsk State Technical University, Russia

    1 publications · 87 citations

    1

    h-index

  5. MH
    Manuela Hummel

    German Cancer Research Center, Germany

    1 publications · 74 citations

    1

    h-index

1–5 of 24

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 2 publications · 27 citations

    2

    h-index

  2. PLoS ONE

    1 publications · 74 citations

    1

    h-index

  3. 1

    h-index

  4. IEEE Computer Graphics and Applications

    1 publications · 83 citations

    1

    h-index

  5. International Journal of STEM Education

    1 publications · 35 citations

    1

    h-index

1–5