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Related Experiment Videos

Interactive tree comparison for co-located collaborative information visualization.

Petra Isenberg1, Sheelagh Carpendale

  • 1University of Calagary. pneumann@cpsc.ucalgary.ca

IEEE Transactions on Visualization and Computer Graphics
|October 31, 2007
PubMed
Summary
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Collaborative information visualization enhances innovation and data analysis. New systems support small groups using interactive tabletops for shared and individual data exploration.

Area of Science:

  • Human-Computer Interaction
  • Information Visualization
  • Collaborative Systems

Background:

  • Collaboration drives innovation through shared knowledge and diverse perspectives.
  • Analyzing information visualizations collaboratively enhances data processing and interpretation.
  • Designing effective collaborative information visualization systems presents unique challenges.

Purpose of the Study:

  • To analyze challenges and requirements for co-located collaborative information visualization.
  • To present a new system supporting collaborative hierarchical data comparison.
  • To facilitate group work around information visualizations on shared interactive displays.

Main Methods:

  • Analysis of design challenges for co-located collaborative information visualization.

Related Experiment Videos

  • Development of a novel system for hierarchical data comparison tasks.
  • Implementation of multi-user input and flexible visualization views.

    • Main Results:

    • The developed system supports shared and individual views on hierarchical data.
    • It enables flexible use of representations and workspace organization for group work.
    • The system is designed for co-located small groups using interactive tabletops.

    Conclusions:

    • Effective design of collaborative information visualization systems is crucial for group analysis.
    • Interactive tabletops can facilitate co-located collaborative data exploration.
    • The presented system offers a flexible and supportive environment for collaborative data comparison.