Publications

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

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

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.

I. Kolesar, S. Bruckner, I. Viola, and H. Hauser, "A Fractional Cartesian Composition Model for Semi-spatial Comparative Visualization Design," IEEE Transactions on Visualization and Computer Graphics, vol. 23, iss. 1, p. 851–860, 2017. doi:10.1109/TVCG.2016.2598870
[BibTeX]

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.
@ARTICLE {Kolesar-2017-FCC,
author = "Ivan Kolesar and Stefan Bruckner and Ivan Viola and Helwig Hauser",
title = "A Fractional Cartesian Composition Model for Semi-spatial Comparative Visualization Design",
journal = "IEEE Transactions on Visualization and Computer Graphics",
year = "2017",
volume = "23",
number = "1",
pages = "851--860",
month = "jan",
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.",
pdf = "pdfs/Kolesar-2017-FCC.pdf",
images = "images/Kolesar-2017-FCC.jpg",
thumbnails = "images/Kolesar-2017-FCC.png",
youtube = "https://www.youtube.com/watch?v=_zk67fmryok",
doi = "10.1109/TVCG.2016.2598870",
event = "IEEE SciVis 2016",
keywords = "visualization models, integrating spatial and non-spatial data visualization, design methodologies",
location = "Baltimore, USA",
project = "physioillustration"
}
projectidphysioillustrationprojectid

Media

Downloads

Full paper [PDF]