EnsembleGraph: Interactive visual analysis of spatiotemporal behaviors in ensemble simulation data

Shu, Q; Guo, H; Liang, J; Che, L; Liu, J; Yuan, X

EnsembleGraph: Interactive visual analysis of spatiotemporal behaviors in ensemble simulation data

Shu, Q Guo, H Liang, J

Che, L Liu, J Yuan, X

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Publication Type:: Conference Proceeding
Citation:: IEEE Pacific Visualization Symposium, 2016, 2016-May pp. 56 - 63
Issue Date:: 2016-05-04

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Field	Value	Language
dc.contributor.author	Shu, Q	en_US
dc.contributor.author	Guo, H	en_US
dc.contributor.author	Liang, J https://orcid.org/0000-0001-7179-5208	en_US
dc.contributor.author	Che, L	en_US
dc.contributor.author	Liu, J	en_US
dc.contributor.author	Yuan, X	en_US
dc.date.issued	2016-05-04	en_US
dc.identifier.citation	IEEE Pacific Visualization Symposium, 2016, 2016-May pp. 56 - 63	en_US
dc.identifier.isbn	9781509014514	en_US
dc.identifier.issn	2165-8765	en_US
dc.identifier.uri	http://hdl.handle.net/10453/116125
dc.description.abstract	© 2016 IEEE. This paper presents a novel visual analysis tool, EnsembleGraph, which aims at helping scientists understand spatiotemporal similarities across runs in time-varying ensemble simulation data. We abstract the input data into a graph, where each node represents a region with similar behaviors across runs and nodes in adjacent time frames are linked if their regions overlap spatially. The visualization of this graph, combined with multiple-linked views showing details, enables users to explore, select, and compare the extracted regions that have similar behaviors. The driving application of this paper is the study of regional emission influences over tropospheric ozone, based on the ensemble simulations conducted with different anthropogenic emission absences using MOZART-4. We demonstrate the effectiveness of our method by visualizing the MOZART-4 ensemble simulation data and evaluating the relative regional emission influences on tropospheric ozone concentrations.	en_US
dc.relation.ispartof	IEEE Pacific Visualization Symposium	en_US
dc.relation.isbasedon	10.1109/PACIFICVIS.2016.7465251	en_US
dc.title	EnsembleGraph: Interactive visual analysis of spatiotemporal behaviors in ensemble simulation data	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2016-May	en_US
utslib.for	080602 Computer-Human Interaction	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	2016-May	en_US

Abstract:

© 2016 IEEE. This paper presents a novel visual analysis tool, EnsembleGraph, which aims at helping scientists understand spatiotemporal similarities across runs in time-varying ensemble simulation data. We abstract the input data into a graph, where each node represents a region with similar behaviors across runs and nodes in adjacent time frames are linked if their regions overlap spatially. The visualization of this graph, combined with multiple-linked views showing details, enables users to explore, select, and compare the extracted regions that have similar behaviors. The driving application of this paper is the study of regional emission influences over tropospheric ozone, based on the ensemble simulations conducted with different anthropogenic emission absences using MOZART-4. We demonstrate the effectiveness of our method by visualizing the MOZART-4 ensemble simulation data and evaluating the relative regional emission influences on tropospheric ozone concentrations.

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http://hdl.handle.net/10453/116125