A Space-Efficient Method for Navigable Ensemble Analysis and Visualization

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dc.contributor.authorHota, Aloken_US
dc.contributor.authorRaji, Mohammaden_US
dc.contributor.authorHobson, Tanneren_US
dc.contributor.authorHuang, Jianen_US
dc.contributor.editorAlexandru Telea and Janine Bennetten_US
dc.date.accessioned2017-06-12T05:12:23Z
dc.date.available2017-06-12T05:12:23Z
dc.date.issued2017
dc.description.abstractScientists increasingly rely on simulation runs of complex models in lieu of cost-prohibitive or infeasible experimentation. The data output of many controlled simulation runs, the ensemble, is used to verify correctness and quantify uncertainty. However, due to their size and complexity, ensembles are difficult to visually analyze because the working set often exceeds strict memory limitations.We present a navigable ensemble analysis tool, NEA, for interactive exploration of ensembles. NEA's pre-processing component takes advantage of the data similarity characteristics of ensembles to represent the data in a new, spatially-efficient data structure which does not require fully reconstructing the original data at visualization time. This data structure allows a fine degree of control in working set management, which enables interactive ensemble exploration while fitting within memory limitations. Scientists can also gain new insights from the data-similarity analysis in the pre-processing component.en_US
dc.description.sectionheadersExploratory Techniques
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualization
dc.identifier.doi10.2312/pgv.20171092
dc.identifier.isbn978-3-03868-034-5
dc.identifier.issn1727-348X
dc.identifier.pages41-51
dc.identifier.urihttps://doi.org/10.2312/pgv.20171092
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/pgv20171092
dc.publisherThe Eurographics Associationen_US
dc.subjectVisualization [Human
dc.subjectcentered computing]
dc.subjectVisualization application domains
dc.subjectScientific visualization
dc.titleA Space-Efficient Method for Navigable Ensemble Analysis and Visualizationen_US
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EGPGV17: Eurographics Symposium on Parallel Graphics and Visualization