Uncertainty In Network Visualization

Uncertainty in Network Visualization is a research subfield of uncertainty visualization that investigates principles, models, and techniques for representing, quantifying, and communicating uncertainty in graph-structured data and their visual encodings, including uncertainties in nodes, edges, attributes, and network layouts.

11

Publications

363

Citations

50

Authors

21

Institutions

Publications per year

2017–2026

3

Authors

50

  1. DW
    Daniel Weiskopf

    University of Stuttgart, Germany

    2 publications · 70 citations

    2

    h-index

  2. JN
    Joseph N. Boyer

    Florida International University, United States

    1 publications · 30 citations

    1

    h-index

  3. AN
    Arlind Nocaj

    University of Konstanz, Germany

    1 publications · 60 citations

    1

    h-index

  4. KZ
    Karl Zilles

    Heinrich Heine University Düsseldorf, Germany

    1 publications · 16 citations

    1

    h-index

  5. AV
    Anette von Kapri

    RWTH Aachen University, Germany

    1 publications · 16 citations

    1

    h-index

1–5 of 50

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 3 publications · 143 citations

    3

    h-index

  2. Journal of Computer Languages

    2 publications · 29 citations

    2

    h-index

  3. 1

    h-index

  4. Nature Biotechnology

    1 publications · 106 citations

    1

    h-index

  5. Estuarine Coastal and Shelf Science

    1 publications · 30 citations

    1

    h-index

1–5