Streaming Data Visualization

Streaming Data Visualization is a method within the broader field of data visualization that enables the real-time graphical representation and continuous updating of temporal data as it is generated, distinguishing it from static or batch-oriented visualization approaches by its inherent support for dynamic, time-vary indicate3d data streams.

57

Publications

2.2K

Citations

191

Authors

79

Institutions

Publications per year

2017–2026

10

Authors

191

  1. MK
    Miloš Krstajić

    University of Konstanz, Germany

    4 publications · 236 citations

    4

    h-index

  2. DA
    Daniel A. Keim

    University of Konstanz, Germany

    4 publications · 243 citations

    4

    h-index

  3. KM
    Kwan‐Liu Ma

    University of California, Davis, United States

    3 publications · 167 citations

    3

    h-index

  4. JA
    Jamal Alsakran

    Kent State University, United States

    2 publications · 95 citations

    2

    h-index

  5. KM
    Ken Martin

    Kitware (United States), United States

    2 publications · 44 citations

    2

    h-index

1–5 of 191

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 9 publications · 832 citations

    9

    h-index

  2. Computer Graphics Forum

    4 publications · 100 citations

    4

    h-index

  3. eScholarship (California Digital Library)

    Repository · 2 publications · 25 citations

    2

    h-index

  4. 2

    h-index

  5. IEEE Computer Graphics and Applications

    2 publications · 67 citations

    2

    h-index

1–5