Irregular Time Series Visualization

Irregular Time Series Visualization is a method of visualizing time-series data in which observations are recorded at non-uniform or unevenly spaced time intervals, distinguishing it from regular time series visualization by explicitly addressing the challenges of temporal irregularity in data acquisition and representation.

6

Publications

252

Citations

23

Authors

10

Institutions

Publications per year

2017–2026

1

Authors

23

  1. MC
    Myoungsu Cho

    Seoul National University, South Korea

    1 publications · 28 citations

    1

    h-index

  2. HA
    Hua Ai

    University of Pittsburgh, United States

    1 publications · 25 citations

    1

    h-index

  3. WH
    William Halsey

    Oak Ridge National Laboratory, United States

    1 publications · 46 citations

    1

    h-index

  4. KG
    Kelly Gaither

    The University of Texas at Austin, United States

    1 publications · 25 citations

    1

    h-index

  5. HB
    Hee‐Joon Bae

    Seoul National University Bundang Hospital, South Korea

    1 publications · 28 citations

    1

    h-index

1–5 of 23

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 2 publications · 53 citations

    2

    h-index

  2. Computers & Graphics

    1 publications · 46 citations

    1

    h-index

  3. ICLS

    1 publications · 25 citations

    1

    h-index

  4. 1

    h-index

1–4