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A Fractional Cartesian Composition Model for Semi-spatial Comparative Visualization Design

I. Kolesar, S. Bruckner, I. Viola, H. Hauser

ARTICLE, IEEE Transactions on Visualization and Computer Graphics, Jan, 2017

Abstract

The study of spatial data ensembles leads to substantial visualization challenges in a variety of applications. In this paper, we present a model for comparative visualization that supports the design of according ensemble visualization solutions by partial automation. We focus on applications, where the user is interested in preserving selected spatial data characteristics of the data as much as possible—even when many ensemble members should be jointly studied using comparative visualization. In our model, we separate the design challenge into a minimal set of user-specified parameters and an optimization component for the automatic configuration of the remaining design variables. We provide an illustrated formal description of our model and exemplify our approach in the context of several application examples from different domains in order to demonstrate its generality within the class of comparative visualization problems for spatial data ensembles.

Published

IEEE Transactions on Visualization and Computer Graphics

  • Volume: 23
  • Number: 1
  • Pages: 1-1
  • Publisher: IEEE
  • ISSN: 1077-2626
  • Date: Jan 2017
  • Project: physioillustration

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BibTeX

@ARTICLE{Kolesar-2017-FCP, 
author={I. Kolesar and S. Bruckner and I. Viola and H. Hauser}, 
journal={IEEE Transactions on Visualization and Computer Graphics}, 
title={A Fractional Cartesian Composition Model for Semi-spatial Comparative Visualization Design}, 
year={2017}, 
volume={23}, 
number={1}, 
pages={1-1}, 
publisher = {IEEE},
note = {Accepted for publication, presented at IEEE SciVis 2016},
abstract={The study of spatial data ensembles leads to substantial visualization challenges in a
 variety of applications. In this paper, we present a model for comparative visualization that
 supports the design of according ensemble visualization solutions by partial automation. We
 focus on applications, where the user is interested in preserving selected spatial data
 characteristics of the data as much as possible—even when many ensemble members should be
 jointly studied using comparative visualization. In our model, we separate the design challenge
 into a minimal set of user-specified parameters and an optimization component for the automatic
 configuration of the remaining design variables. We provide an illustrated formal description of
 our model and exemplify our approach in the context of several application examples from different
 domains in order to demonstrate its generality within the class of comparative visualization
 problems for spatial data ensembles.}, 
keywords={Computational modeling;Data models;Data visualization;Encoding;Spatial databases;
Three-dimensional displays;Visualization;Design Methodologies;Integrating Spatial and
 Non-Spatial Data Visualization;Visualization Models}, 
doi={10.1109/TVCG.2016.2598870}, 
ISSN={1077-2626}, 
month={Jan},



}






 Last Modified: Jean-Paul Balabanian, 2017-06-30