Uncertainty Metrics

Uncertainty Metrics is a quantitative framework used in scientific visualization to characterize the nature, magnitude, and structure of uncertainty in data and visual representations, distinguishing itself by systematically formalizing how uncertainty is measured, classified, and communicated within visual analysis contexts.

113

Publications

6.3K

Citations

377

Authors

179

Institutions

Publications per year

2017–2026

59

Authors

377

  1. HJ
    Heather J. Kulik

    Massachusetts Institute of Technology, United States

    3 publications · 286 citations

    3

    h-index

  2. CD
    Chenru Duan

    Massachusetts Institute of Technology, United States

    3 publications · 286 citations

    3

    h-index

  3. AF
    Apostolos F. Psaros

    Columbia University, United States

    2 publications · 410 citations

    2

    h-index

  4. SB
    Sifeng Bi

    Leibniz University Hannover, Germany

    2 publications · 180 citations

    2

    h-index

  5. HA
    Hamzeh Asgharnezhad

    Deakin University, Australia

    2 publications · 91 citations

    2

    h-index

1–5 of 377

Venues

  1. arXiv (Cornell University)

    Repository · 6 publications · 204 citations

    6

    h-index

  2. Reliability Engineering & System Safety

    4 publications · 312 citations

    4

    h-index

  3. Remote Sensing

    3 publications · 148 citations

    3

    h-index

  4. IEEE Computer Graphics and Applications

    3 publications · 342 citations

    3

    h-index

  5. Measurement Science and Technology

    3 publications · 288 citations

    3

    h-index

1–5