“T-Map: Time-Varying Volume Data Mining Based on Topological Feature Analysis”

Volume visualization has served as an indispensable tool for peering into the inner structures of volumetric datasets. However, there exist a few reports on how to visualize effectively time-varying volume datasets, which arise frequently in a variety of numerical simulations and measurements. In this paper, the concept of volume data mining is extended to propose an environment, termed T-map, for visually exploring a large-scale time-varying volume dataset, where a pixel-oriented information visualization technique is employed so that the users are allowed to interactively specify partial spatiotemporal regions with characteristic change in topological structures prior to detailed and comprehensible volume visualization processes. A case study with a dataset from atomic collision research is performed to illustrate the feasibility of the present method.