Interactive Time-series Exploration

Interactive Time-Series Exploration is a computational framework that enables dynamic, user-driven manipulation and real-time visual analysis of temporal data to facilitate the discovery of patterns, anomalies, and structural relationships through iterative querying, zooming, filtering, and coordinated views.

86

Publications

3.6K

Citations

276

Authors

125

Institutions

Publications per year

2017–2026

24

Authors

276

  1. NA
    Natalia Andrienko

    Fraunhofer Institute for Intelligent Analysis and Information Systems, Germany

    5 publications · 164 citations

    5

    h-index

  2. GA
    Gennady Andrienko

    Fraunhofer Institute for Intelligent Analysis and Information Systems, Germany

    5 publications · 164 citations

    5

    h-index

  3. MW
    Mark W. Jones

    Swansea University, United Kingdom

    4 publications · 299 citations

    4

    h-index

  4. HH
    Harry Hochheiser

    University of Pittsburgh, United States

    4 publications · 324 citations

    4

    h-index

  5. BS
    Ben Shneiderman

    University of Maryland, College Park, United States

    3 publications · 305 citations

    3

    h-index

1–5 of 276

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 13 publications · 615 citations

    13

    h-index

  2. Computer Graphics Forum

    4 publications · 60 citations

    4

    h-index

  3. Information Visualization

    3 publications · 214 citations

    3

    h-index

  4. 3

    h-index

  5. The Visual Computer

    2 publications · 119 citations

    2

    h-index

1–5