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Volume: 29 | Article ID: art00011
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Effectiveness of Feature-Driven Storytelling in 3D Time-Varying Data Visualization
  DOI :  10.2352/ISSN.2470-1173.2017.1.VDA-393  Published OnlineJanuary 2017
Abstract

Storytelling animation has a great potential to be widely adopted by domain scientists for exploring trends in scientific simulations. However, due to the dynamic nature and generation methods of animations, serious concerns have been raised regarding their effectiveness for analytical tasks. This has led to interactive techniques often being favored over animations, as they provide the user with complete control over the visualization. This trend in scientific visualization design has not yet considered newer algorithmic animation generation methods that are driven by the automatic analysis of data features and storytelling techniques. In this work, the authors performed an experiment which compares feature-driven storytelling animations to common interactive visualization techniques for time-varying scientific simulations. They discuss the design of the experiment, including tasks for storm-surge analysis that are representative of common scientific visualization projects. Their results illustrate the relative advantages of both feature-driven storytelling animations and interactive visualizations, which may provide useful design guidelines for future storytelling and scientific visualization techniques. © 2016 Society for Imaging Science and Technology.

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Li Yu, Lane Harrison, Aidong Lu, "Effectiveness of Feature-Driven Storytelling in 3D Time-Varying Data Visualizationin Proc. IS&T Int’l. Symp. on Electronic Imaging: Visualization and Data Analysis,  2017,  pp 99 - 109,  https://doi.org/10.2352/ISSN.2470-1173.2017.1.VDA-393

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Copyright © Society for Imaging Science and Technology 2017
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