Preserving Contextual Awareness during Selection of Moving Targets in Animated Stream Visualizations

Eric D. Ragan, Andrew Pachuilo, John R. Goodall, Felipe Bacim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In many types of dynamic interactive visualizations, it is often desired to interact with moving objects. Stopping moving objects can make selection easier, but pausing animated content can disrupt perception and understanding of the visualization. To address such problems, we explore selection techniques that only pause a subset of all moving targets in the visualization. We present various designs for controlling pause regions based on cursor trajectory or cursor position. We then report a dual-task experiment that evaluates how different techniques affect both target selection performance and contextual awareness of the visualization. Our findings indicate that all pause techniques significantly improved selection performance as compared to the baseline method without pause, but the results also show that pausing the entire visualization can interfere with contextual awareness. However, the problem with reduced contextual awareness was not observed with our new techniques that only pause a limited region of the visualization. Thus, our research provides evidence that region-limited pause techniques can retain the advantages of selection in dynamic visualizations without imposing a negative effect on contextual awareness.

Original languageEnglish
Title of host publicationProceedings of the Working Conference on Advanced Visual Interfaces, AVI 2020
EditorsGenny Tortora, Giuliana Vitiello, Marco Winckler
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450375351
DOIs
StatePublished - Sep 28 2020
Event2020 International Conference on Advanced Visual Interfaces, AVI 2020 - Salerno, Italy
Duration: Sep 28 2020Oct 2 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2020 International Conference on Advanced Visual Interfaces, AVI 2020
Country/TerritoryItaly
CitySalerno
Period09/28/2010/2/20

Funding

This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan http://energy.gov/downloads/doe-public-access-plan. This research is supported in part by the DARPA XAI program under Grant N66001-17-2-4032.

FundersFunder number
U.S. Department of Energy
Defense Advanced Research Projects AgencyN66001-17-2-4032

    Keywords

    • Visualization
    • animation
    • human-computer interaction
    • information visualization
    • selection techniques
    • streaming data

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