Nested Tracking Graphs

Tracking graphs are a well established tool in topological analysis to visualize the evolution of components and their properties over time, i.e., when components appear, disappear, merge, and split. However, tracking graphs are limited to a single level threshold and the graphs may vary substantial...

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Vydané v:Computer graphics forum Ročník 36; číslo 3; s. 12 - 22
Hlavní autori: Lukasczyk, Jonas, Weber, Gunther, Maciejewski, Ross, Garth, Christoph, Leitte, Heike
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Blackwell Publishing Ltd 01.06.2017
Wiley
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Categories and Subject Descriptors (according to ACM CCS)
Computational fluid dynamics
Computer simulation
Cosmology
Data [Computer Graphics]: Data Structures—Graphs and Networks
Graphs
MATHEMATICS AND COMPUTING
Nesting
Topology
Tracking
ISSN:0167-7055, 1467-8659
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Popis
Shrnutí:Tracking graphs are a well established tool in topological analysis to visualize the evolution of components and their properties over time, i.e., when components appear, disappear, merge, and split. However, tracking graphs are limited to a single level threshold and the graphs may vary substantially even under small changes to the threshold. To examine the evolution of features for varying levels, users have to compare multiple tracking graphs without a direct visual link between them. We propose a novel, interactive, nested graph visualization based on the fact that the tracked superlevel set components for different levels are related to each other through their nesting hierarchy. This approach allows us to set multiple tracking graphs in context to each other and enables users to effectively follow the evolution of components for different levels simultaneously. We demonstrate the effectiveness of our approach on datasets from finite pointset methods, computational fluid dynamics, and cosmology simulations.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
AC02-05CH11231
ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.13164