Exploring ensemble visualization

Madhura N. Phadke; Lifford Pinto; Oluwafemi Alabi; Jonathan Harter; Russell M. Taylor II; Xunlei Wu; Hannah Petersen; Steffen A. Bass; Christopher G. Healey

doi:10.1117/12.912419

24 January 2012 Exploring ensemble visualization

Madhura N. Phadke, Lifford Pinto, Oluwafemi Alabi, Jonathan Harter, Russell M. Taylor II, Xunlei Wu, Hannah Petersen, Steffen A. Bass, Christopher G. Healey

Author Affiliations +

Proceedings Volume 8294, Visualization and Data Analysis 2012; 82940B (2012) https://doi.org/10.1117/12.912419
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

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.

Citation Download Citation

Madhura N. Phadke, Lifford Pinto, Oluwafemi Alabi, Jonathan Harter, Russell M. Taylor II, Xunlei Wu, Hannah Petersen, Steffen A. Bass, and Christopher G. Healey "Exploring ensemble visualization", Proc. SPIE 8294, Visualization and Data Analysis 2012, 82940B (24 January 2012); https://doi.org/10.1117/12.912419

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