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Proceedings Paper

Exploring ensemble visualization
Author(s): Madhura N. Phadke; Lifford Pinto; Oluwafemi Alabi; Jonathan Harter; Russell M. Taylor; Xunlei Wu; Hannah Petersen; Steffen A. Bass; Christopher G. Healey
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Paper Abstract

An ensemble is a collection of related datasets. Each dataset, or member, of an ensemble is normally large, multidimensional, and spatio-temporal. Ensembles are used extensively by scientists and mathematicians, for example, by executing a simulation repeatedly with slightly different input parameters and saving the results in an ensemble to see how parameter choices affect the simulation. To draw inferences from an ensemble, scientists need to compare data both within and between ensemble members. We propose two techniques to support ensemble exploration and comparison: a pairwise sequential animation method that visualizes locally neighboring members simultaneously, and a screen door tinting method that visualizes subsets of members using screen space subdivision. We demonstrate the capabilities of both techniques, first using synthetic data, then with simulation data of heavy ion collisions in high-energy physics. Results show that both techniques are capable of supporting meaningful comparisons of ensemble data.

Paper Details

Date Published: 24 January 2012
PDF: 12 pages
Proc. SPIE 8294, Visualization and Data Analysis 2012, 82940B (24 January 2012); doi: 10.1117/12.912419
Show Author Affiliations
Madhura N. Phadke, North Carolina State Univ. (United States)
Lifford Pinto, North Carolina State Univ. (United States)
Oluwafemi Alabi, The Univ. of North Carolina at Chapel Hill (United States)
Jonathan Harter, The Univ. of North Carolina at Chapel Hill (United States)
Russell M. Taylor, The Univ. of North Carolina at Chapel Hill (United States)
Xunlei Wu, Renaissance Computing Institute (United States)
Hannah Petersen, Duke Univ. (United States)
Steffen A. Bass, Duke Univ. (United States)
Christopher G. Healey, North Carolina State Univ. (United States)

Published in SPIE Proceedings Vol. 8294:
Visualization and Data Analysis 2012
Pak Chung Wong; David L. Kao; Ming C. Hao; Chaomei Chen; Robert Kosara; Mark A. Livingston; Jinah Park; Ian Roberts, Editor(s)

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