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Title: Exploring Time-Varying Multivariate Volume Data Using Matrix of Isosurface Similarity Maps

Abstract

We present a novel visual representation and interface named the matrix of isosurface similarity maps (MISM) for effective exploration of large time-varying multivariate volumetric data sets. MISM synthesizes three types of similarity maps (i.e., self, temporal, and variable similarity maps) to capture the essential relationships among isosurfaces of different variables and time steps. Additionally, it serves as the main visual mapping and navigation tool for examining the vast number of isosurfaces and exploring the underlying time-varying multivariate data set. We present temporal clustering, variable grouping, and interactive filtering to reduce the huge exploration space of MISM. In conjunction with the isovalue and isosurface views, MISM allows users to identify important isosurfaces or isosurface pairs and compare them over space, time, and value range. More importantly, we introduce path recommendation that suggests, animates, and compares traversal paths for effectively exploring MISM under varied criteria and at different levels-of-detail. A silhouette-based method is applied to render multiple surfaces of interest in a visually succinct manner. We demonstrate the effectiveness of our approach with case studies of several time-varying multivariate data sets and an ensemble data set, and evaluate our work with two domain experts.

Authors:
 [1];  [1];  [1];  [1];  [2];  [2];  [3]
  1. Univ. of Notre Dame, IN (United States)
  2. Argonne National Lab. (ANL), Argonne, IL (United States)
  3. The Ohio State Univ., Columbus, OH (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
National Science Foundation (NSF); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
OSTI Identifier:
1510060
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
IEEE Transactions on Visualization and Computer Graphics
Additional Journal Information:
Journal Volume: 25; Journal Issue: 1; Journal ID: ISSN 1077-2626
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; Time-varying multivariate data visualization; isosurface; path recommendation; similarity map; visual interface

Citation Formats

Tao, Jun, Imre, Martin, Wang, Chaoli, Chawla, Nitesh V., Guo, Hanqi, Sever, Gökhan, and Kim, Seung Hyun. Exploring Time-Varying Multivariate Volume Data Using Matrix of Isosurface Similarity Maps. United States: N. p., 2019. Web. doi:10.1109/TVCG.2018.2864808.
Tao, Jun, Imre, Martin, Wang, Chaoli, Chawla, Nitesh V., Guo, Hanqi, Sever, Gökhan, & Kim, Seung Hyun. Exploring Time-Varying Multivariate Volume Data Using Matrix of Isosurface Similarity Maps. United States. https://doi.org/10.1109/TVCG.2018.2864808
Tao, Jun, Imre, Martin, Wang, Chaoli, Chawla, Nitesh V., Guo, Hanqi, Sever, Gökhan, and Kim, Seung Hyun. 2019. "Exploring Time-Varying Multivariate Volume Data Using Matrix of Isosurface Similarity Maps". United States. https://doi.org/10.1109/TVCG.2018.2864808. https://www.osti.gov/servlets/purl/1510060.
@article{osti_1510060,
title = {Exploring Time-Varying Multivariate Volume Data Using Matrix of Isosurface Similarity Maps},
author = {Tao, Jun and Imre, Martin and Wang, Chaoli and Chawla, Nitesh V. and Guo, Hanqi and Sever, Gökhan and Kim, Seung Hyun},
abstractNote = {We present a novel visual representation and interface named the matrix of isosurface similarity maps (MISM) for effective exploration of large time-varying multivariate volumetric data sets. MISM synthesizes three types of similarity maps (i.e., self, temporal, and variable similarity maps) to capture the essential relationships among isosurfaces of different variables and time steps. Additionally, it serves as the main visual mapping and navigation tool for examining the vast number of isosurfaces and exploring the underlying time-varying multivariate data set. We present temporal clustering, variable grouping, and interactive filtering to reduce the huge exploration space of MISM. In conjunction with the isovalue and isosurface views, MISM allows users to identify important isosurfaces or isosurface pairs and compare them over space, time, and value range. More importantly, we introduce path recommendation that suggests, animates, and compares traversal paths for effectively exploring MISM under varied criteria and at different levels-of-detail. A silhouette-based method is applied to render multiple surfaces of interest in a visually succinct manner. We demonstrate the effectiveness of our approach with case studies of several time-varying multivariate data sets and an ensemble data set, and evaluate our work with two domain experts.},
doi = {10.1109/TVCG.2018.2864808},
url = {https://www.osti.gov/biblio/1510060}, journal = {IEEE Transactions on Visualization and Computer Graphics},
issn = {1077-2626},
number = 1,
volume = 25,
place = {United States},
year = {Tue Jan 01 00:00:00 EST 2019},
month = {Tue Jan 01 00:00:00 EST 2019}
}

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Works referencing / citing this record:

Event-based exploration and comparison on time-varying ensembles
journal, October 2019