Issue No. 12 - Dec. (2011 vol. 17)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2011.246
Yi Gu , Michigan Technological University
Chaoli Wang , Michigan Technological University
A fundamental challenge for time-varying volume data analysis and visualization is the lack of capability to observe and track data change or evolution in an occlusion-free, controllable, and adaptive fashion. In this paper, we propose to organize a timevarying data set into a hierarchy of states. By deriving transition probabilities among states, we construct a global map that captures the essential transition relationships in the time-varying data. We introduce the TransGraph, a graph-based representation to visualize hierarchical state transition relationships. The TransGraph not only provides a visual mapping that abstracts data evolution over time in different levels of detail, but also serves as a navigation tool that guides data exploration and tracking. The user interacts with the TransGraph and makes connection to the volumetric data through brushing and linking. A set of intuitive queries is provided to enable knowledge extraction from time-varying data. We test our approach with time-varying data sets of different characteristics and the results show that the TransGraph can effectively augment our ability in understanding time-varying data.
Time-varying data visualization, hierarchical representation, states, transition relationship, user interface.
C. Wang and Y. Gu, "TransGraph: Hierarchical Exploration of Transition Relationships in Time-Varying Volumetric Data," in IEEE Transactions on Visualization & Computer Graphics, vol. 17, no. , pp. 2015-2024, 2011.