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Proceedings Paper

Ensemble visual analysis architecture with high mobility for large-scale critical infrastructure simulations
Author(s): Todd Eaglin; Xiaoyu Wang; William Ribarsky; William Tolone
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Paper Abstract

Nowhere is the need to understand large heterogeneous datasets more important than in disaster monitoring and emergency response, where critical decisions have to be made in a timely fashion and the discovery of important events requires an understanding of a collection of complex simulations. To gain enough insights for actionable knowledge, the development of models and analysis of modeling results usually requires that models be run many times so that all possibilities can be covered. Central to the goal of our research is, therefore, the use of ensemble visualization of a large scale simulation space to appropriately aid decision makers in reasoning about infrastructure behaviors and vulnerabilities in support of critical infrastructure analysis. This requires the bringing together of computing-driven simulation results with the human decision-making process via interactive visual analysis. We have developed a general critical infrastructure simulation and analysis system for situationally aware emergency response during natural disasters. Our system demonstrates a scalable visual analytics infrastructure with mobile interface for analysis, visualization and interaction with large-scale simulation results in order to better understand their inherent structure and predictive capabilities. To generalize the mobile aspect, we introduce mobility as a design consideration for the system. The utility and efficacy of this research has been evaluated by domain practitioners and disaster response managers.

Paper Details

Date Published: 8 February 2015
PDF: 15 pages
Proc. SPIE 9397, Visualization and Data Analysis 2015, 939706 (8 February 2015); doi: 10.1117/12.2076472
Show Author Affiliations
Todd Eaglin, The Univ. of North Carolina at Charlotte (United States)
Xiaoyu Wang, The Univ. of North Carolina at Charlotte (United States)
William Ribarsky, The Univ. of North Carolina at Charlotte (United States)
William Tolone, The Univ. of North Carolina at Charlotte (United States)

Published in SPIE Proceedings Vol. 9397:
Visualization and Data Analysis 2015
David L. Kao; Ming C. Hao; Mark A. Livingston; Thomas Wischgoll, Editor(s)

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