Data Provenance Visualization

Data Provenance Visualization is a visual representation method that explicitly encodes the origin, transformation history, and contextual lineage of data elements to enable transparent, traceable, and interpretable analysis within visual data exploration processes.

23

Publications

949

Citations

96

Authors

45

Institutions

Publications per year

2017–2026

10

Authors

96

  1. BP
    Beth Plale

    Indiana University Bloomington, United States

    4 publications · 120 citations

    4

    h-index

  2. SA
    Scott A. Jensen

    San Jose State University, United States

    2 publications · 73 citations

    2

    h-index

  3. YL
    Yuan Luo

    Northwestern University, United States

    2 publications · 73 citations

    2

    h-index

  4. MS
    Mehmet S. Aktaş

    Yıldız Technical University, Türkiye

    2 publications · 42 citations

    2

    h-index

  5. MS
    Marc Streit

    Johannes Kepler University of Linz, Austria

    2 publications · 171 citations

    2

    h-index

1–5 of 96

Venues

  1. Computer Graphics Forum

    2 publications · 171 citations

    2

    h-index

  2. 1

    h-index

  3. IEEE Computer Graphics and Applications

    1 publications · 35 citations

    1

    h-index

  4. Procedia Computer Science

    1 publications · 25 citations

    1

    h-index

  5. 1

    h-index

1–5