TY - GEN
T1 - Hierarchical causality explorer
T2 - Visualization and Data Analysis 2006
AU - Azuma, Shizuka
AU - Fujishiro, Issei
AU - Horii, Hideyuki
PY - 2006/4/17
Y1 - 2006/4/17
N2 - 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.
AB - 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.
KW - Cognitive map
KW - ConeTrees
KW - DiskTrees
KW - Hierarchical causality
KW - Information visualization
UR - http://www.scopus.com/inward/record.url?scp=33645683874&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33645683874&partnerID=8YFLogxK
U2 - 10.1117/12.650934
DO - 10.1117/12.650934
M3 - Conference contribution
AN - SCOPUS:33645683874
SN - 0819461008
SN - 9780819461001
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Visualization and Data Analysis 2006 - Proceedings of SPIE-IS and T Electronic Imaging
Y2 - 16 January 2006 through 17 January 2006
ER -