Feature-Driven Visual Analytics of Chaotic Parameter-Dependent Movement

Analyzing movements in their spatial and temporal context is a complex task. We are additionally interested in understanding the movements’ dependency on parameters that govern the processes behind the movement. We propose a visual analytics approach combining analytic, visual, and interactive means...

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Vydané v:Computer graphics forum Ročník 34; číslo 3; s. 421 - 430
Hlavní autori: Luboschik, M., Röhlig, M., Bittig, A.T., Andrienko, N., Schumann, H., Tominski, C.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Blackwell Publishing Ltd 01.06.2015
Predmet:
Analysis
Analytics
Categories and Subject Descriptors (according to ACM CCS)
Chaos theory
Computer graphics
Data points
Dynamic tests
Feature extraction
Human-centered computing - Visualization - Visualization application domains - Visual analytics
Interactive
Mathematical analysis
Studies
Tasks
Visual
Visualization
ISSN:0167-7055, 1467-8659
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Popis
Shrnutí:Analyzing movements in their spatial and temporal context is a complex task. We are additionally interested in understanding the movements’ dependency on parameters that govern the processes behind the movement. We propose a visual analytics approach combining analytic, visual, and interactive means to deal with the added complexity. The key idea is to perform an analytical extraction of features that capture distinct movement characteristics. Different parameter configurations and extracted features are then visualized in a compact fashion to facilitate an overview of the data. Interaction enables the user to access details about features, to compare features, and to relate features back to the original movement. We instantiate our approach with a repository of more than twenty accepted and novel features to help analysts in gaining insight into simulations of chaotic behavior of thousands of entities over thousands of data points. Domain experts applied our solution successfully to study dynamic groups in such movements in relation to thousands of parameter configurations.
Bibliografia:Supporting InformationSupporting Information
ArticleID:CGF12654
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SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12654