Concepedia

Collaborative Visual Querying

Collaborative Visual Querying is a collaborative visual analytics method that enables multiple users to jointly formulate, execute, and refine visual queries through shared interactive interfaces, distinguished by its support for concurrent input, real-time feedback, and collective sensemaking over visualized data.

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Publications

19

Citations

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Authors

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Institutions

Publications per year

2017–2026

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Parents

Publications

1

1–2 of 1

Authors

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  1. NE
    Niklas Elmqvist

    University of Maryland, College Park, United States

    1 publications · 19 citations

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    h-index

  2. SX
    Saining Xie

    Meta (Israel), Israel

    1 publications · 36 citations

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    h-index

  3. PW
    Penghao Wu

    Xinjiang Agricultural University, China

    1 publications · 36 citations

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1–3 of 1

Institutions

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  1. Purdue University West Lafayette

    West Lafayette, United States

    1 h-index

    2 publications

    38 citations

  2. University of California San Diego

    San Diego, United States

    1 publications

    36 citations

  3. New York University

    New York, United States

    1 publications

    36 citations

1–3 of 1

Venues

  1. Information Visualization

    1 publications · 19 citations

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    h-index

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