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

Ivan Kolesár, Stefan Bruckner, Ivan Viola, Helwig Hauser

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

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.

Original languageEnglish (US)
Article number7539573
Pages (from-to)851-860
Number of pages10
JournalIEEE Transactions on Visualization and Computer Graphics
Volume23
Issue number1
DOIs
StatePublished - Jan 1 2017
Externally publishedYes

Keywords

  • Design Methodologies
  • Integrating Spatial and Non-Spatial Data Visualization
  • Visualization Models

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

Fingerprint

Dive into the research topics of 'A Fractional Cartesian Composition Model for Semi-Spatial Comparative Visualization Design'. Together they form a unique fingerprint.

Cite this