Missing Data Visualization

Missing Data Visualization is a visualization technique that specifically represents gaps or absent values within temporal data sequences, distinguishing itself by encoding the presence, pattern, and extent of missingness alongside observed time-series observations.

21

Publications

1.3K

Citations

51

Authors

24

Institutions

Publications per year

2017–2026

6

Authors

51

  1. AP
    Alex Pang

    University of California, Santa Cruz, United States

    3 publications · 46 citations

    3

    h-index

  2. SD
    Suzana Djurcilov

    University of California, Santa Cruz, United States

    3 publications · 46 citations

    3

    h-index

  3. HH
    Heike Hofmann

    Iowa State University, United States

    3 publications · 204 citations

    3

    h-index

  4. PF
    Peter Filzmoser

    TU Wien, Austria

    2 publications · 130 citations

    2

    h-index

  5. JC
    John Cavallo

    Goddard Space Flight Center, United States

    2 publications · 30 citations

    2

    h-index

1–5 of 51

Venues

  1. Journal of Computational and Graphical Statistics

    JCGS · 2 publications · 178 citations

    2

    h-index

  2. Journal of Statistical Software

    JSS · 2 publications · 674 citations

    2

    h-index

  3. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 2 publications · 94 citations

    2

    h-index

  4. IEEE Visualization

    Conference · 2 publications · 27 citations

    2

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  5. IEEE Access

    1 publications · 22 citations

    1

    h-index

1–5