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Title: Nested Tracking Graphs

Abstract

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 show the effectiveness of our approach on datasets from finite pointset methods, computational fluid dynamics, and cosmology simulations.

Authors:
 [1];  [2];  [3];  [1];  [1]
  1. Univ. of Kaiserslautern (Germany)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. Arizona State Univ., Tempe, AZ (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1379867
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Computer Graphics Forum
Additional Journal Information:
Journal Volume: 36; Journal Issue: 3; Journal ID: ISSN 0167-7055
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Lukasczyk, Jonas, Weber, Gunther, Maciejewski, Ross, Garth, Christoph, and Leitte, Heike. Nested Tracking Graphs. United States: N. p., 2017. Web. doi:10.1111/cgf.13164.
Lukasczyk, Jonas, Weber, Gunther, Maciejewski, Ross, Garth, Christoph, & Leitte, Heike. Nested Tracking Graphs. United States. doi:10.1111/cgf.13164.
Lukasczyk, Jonas, Weber, Gunther, Maciejewski, Ross, Garth, Christoph, and Leitte, Heike. Thu . "Nested Tracking Graphs". United States. doi:10.1111/cgf.13164. https://www.osti.gov/servlets/purl/1379867.
@article{osti_1379867,
title = {Nested Tracking Graphs},
author = {Lukasczyk, Jonas and Weber, Gunther and Maciejewski, Ross and Garth, Christoph and Leitte, Heike},
abstractNote = {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 show the effectiveness of our approach on datasets from finite pointset methods, computational fluid dynamics, and cosmology simulations.},
doi = {10.1111/cgf.13164},
journal = {Computer Graphics Forum},
number = 3,
volume = 36,
place = {United States},
year = {2017},
month = {6}
}

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Works referenced in this record:

Time-varying reeb graphs for continuous space-time data
conference, January 2004

  • Edelsbrunner, Herbert; Harer, John; Mascarenhas, Ajith
  • Proceedings of the twentieth annual symposium on Computational geometry - SCG '04
  • DOI: 10.1145/997817.997872

Tracking scalar features in unstructured data sets
conference, January 1998


Feature-Based Statistical Analysis of Combustion Simulation Data
journal, December 2011

  • Bennett, Janine C.; Krishnamoorthy, Vaidyanathan
  • IEEE Transactions on Visualization and Computer Graphics, Vol. 17, Issue 12
  • DOI: 10.1109/TVCG.2011.199

Interactive Exploration and Analysis of Large-Scale Simulations Using Topology-Based Data Segmentation
journal, September 2011

  • Bremer, P-T; Weber, G.; Tierny, J.
  • IEEE Transactions on Visualization and Computer Graphics, Vol. 17, Issue 9
  • DOI: 10.1109/TVCG.2010.253

Time-varying contour topology
journal, January 2006

  • Sohn, B. -S.
  • IEEE Transactions on Visualization and Computer Graphics, Vol. 12, Issue 1
  • DOI: 10.1109/TVCG.2006.16

A Survey of Topology-based Methods in Visualization
journal, June 2016

  • Heine, C.; Leitte, H.; Hlawitschka, M.
  • Computer Graphics Forum, Vol. 35, Issue 3
  • DOI: 10.1111/cgf.12933

The Lyman α forest in optically thin hydrodynamical simulations
journal, December 2014

  • Lukić, Zarija; Stark, Casey W.; Nugent, Peter
  • Monthly Notices of the Royal Astronomical Society, Vol. 446, Issue 4
  • DOI: 10.1093/mnras/stu2377

Interactive exploration of large-scale time-varying data using dynamic tracking graphs
conference, October 2012

  • Widanagamaachchi, W.; Christensen, C.; Bremer, P. -T
  • 2012 IEEE Symposium on Large Data Analysis and Visualization (LDAV 2012), IEEE Symposium on Large Data Analysis and Visualization (LDAV)
  • DOI: 10.1109/LDAV.2012.6378962

Computing contour trees in all dimensions
journal, February 2003


Understanding the Structure of the Turbulent Mixing Layer in Hydrodynamic Instabilities
journal, September 2006

  • Laney, D.; Bremer, P. -t.; Mascarenhas, A.
  • IEEE Transactions on Visualization and Computer Graphics, Vol. 12, Issue 5
  • DOI: 10.1109/TVCG.2006.186

Nyx: A MASSIVELY PARALLEL AMR CODE FOR COMPUTATIONAL COSMOLOGY
journal, February 2013


Topological feature extraction and tracking
journal, July 2007


Topology matching for fully automatic similarity estimation of 3D shapes
conference, January 2001

  • Hilaga, Masaki; Shinagawa, Yoshihisa; Kohmura, Taku
  • Proceedings of the 28th annual conference on Computer graphics and interactive techniques - SIGGRAPH '01
  • DOI: 10.1145/383259.383282

Understanding hotspots: a topological visual analytics approach
conference, January 2015

  • Lukasczyk, Jonas; Maciejewski, Ross; Garth, Christoph
  • Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS '15
  • DOI: 10.1145/2820783.2820817

Data-parallel halo finding with variable linking lengths
conference, November 2014

  • Widanagamaachchi, Wathsala; Bremer, Peer-Timo; Sewell, Christopher
  • 2014 IEEE 4th Symposium on Large Data Analysis and Visualization (LDAV)
  • DOI: 10.1109/LDAV.2014.7013201