Hierarchical causality explorer: Making complemental use of 3D/2D visualizations

Shizuka Azuma, Issei Fujishiro, Hideyuki Horii

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Hierarchical causality relationships reside ubiquitously in the reality. Since the relationships take intricate forms with two kinds of links - hierarchical abstraction and causal association, there exists no single visualization style that allows the user to comprehend them effectively. This paper introduces a novel information visualization framework which can change existing 3D and 2D display styles interactively according to the user's visual analysis demands. The two visualization styles play a complementary role, and the change in the style relies on morphing so as to maintain the user's cognitive map. Based on this framework, we have developed a general-purpose prototype system, which provides the user with an enriched set of functions not only for supporting fundamental information seeking, but bridging analytic gaps to accomplishing high-level analytic tasks such as knowledge discovery and decision making. The effectiveness of the system is illustrated with an application to the analysis of a nuclear-hazard cover-up problem.

Original languageEnglish
Title of host publicationVisualization and Data Analysis 2006 - Proceedings of SPIE-IS and T Electronic Imaging
DOIs
Publication statusPublished - 2006 Apr 17
Externally publishedYes
EventVisualization and Data Analysis 2006 - San Jose, CA, United States
Duration: 2006 Jan 162006 Jan 17

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6060
ISSN (Print)0277-786X

Other

OtherVisualization and Data Analysis 2006
Country/TerritoryUnited States
CitySan Jose, CA
Period06/1/1606/1/17

Keywords

  • Cognitive map
  • ConeTrees
  • DiskTrees
  • Hierarchical causality
  • Information visualization

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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