Multiple uncertainties in time-variant cosmological particle data

Steve Haroz; Kwan-Liu Ma; Katrin Heitmann

doi:10.1109/PACIFICVIS.2008.4475478

Multiple uncertainties in time-variant cosmological particle data

Steve Haroz, Kwan-Liu Ma, Katrin Heitmann

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

18 Scopus citations

Abstract

Though the mediums for visualization are limited, the potential dimensions of a dataset are not. In many areas of scientific study, understanding the correlations between those dimensions and their uncertainties is pivotal to mining useful information from a dataset. Obtaining this insight can necessitate visualizing the many relationships among temporal, spatial, and other dimensionalities of data and its uncertainties. We utilize multiple views for interactive dataset exploration and selection of important features, and. we apply those techniques to the unique challenges of cosmological particle datasets. We show how interactivity and incorporation of multiple visualization techniques help overcome the problem of limited visualization dimensions and allow many types of uncertainty to be seen in correlation with other variables.

Original language	English (US)
Title of host publication	IEEE Pacific Visualisation Symposium 2008, PacificVis - Proceedings
Pages	207-214
Number of pages	8
DOIs	https://doi.org/10.1109/PACIFICVIS.2008.4475478
State	Published - Aug 25 2008
Event	2008 Pacific Visualization Symposium, PacificVis 2008 - Kyoto, Japan Duration: Mar 4 2008 → Mar 7 2008

Other

Other	2008 Pacific Visualization Symposium, PacificVis 2008
Country	Japan
City	Kyoto
Period	3/4/08 → 3/7/08

Keywords

Cosmology
Parallel coordinates
Uncertainty visualization
Visualization applications

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Hardware and Architecture
Software

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title = "Multiple uncertainties in time-variant cosmological particle data",

abstract = "Though the mediums for visualization are limited, the potential dimensions of a dataset are not. In many areas of scientific study, understanding the correlations between those dimensions and their uncertainties is pivotal to mining useful information from a dataset. Obtaining this insight can necessitate visualizing the many relationships among temporal, spatial, and other dimensionalities of data and its uncertainties. We utilize multiple views for interactive dataset exploration and selection of important features, and. we apply those techniques to the unique challenges of cosmological particle datasets. We show how interactivity and incorporation of multiple visualization techniques help overcome the problem of limited visualization dimensions and allow many types of uncertainty to be seen in correlation with other variables.",

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AU - Ma, Kwan-Liu

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AB - Though the mediums for visualization are limited, the potential dimensions of a dataset are not. In many areas of scientific study, understanding the correlations between those dimensions and their uncertainties is pivotal to mining useful information from a dataset. Obtaining this insight can necessitate visualizing the many relationships among temporal, spatial, and other dimensionalities of data and its uncertainties. We utilize multiple views for interactive dataset exploration and selection of important features, and. we apply those techniques to the unique challenges of cosmological particle datasets. We show how interactivity and incorporation of multiple visualization techniques help overcome the problem of limited visualization dimensions and allow many types of uncertainty to be seen in correlation with other variables.

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KW - Uncertainty visualization

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