HumMod Browser: An Exploratory Visualization Tool for the Analysis of Whole-Body Physiology Simulation Data

Keqin Wu, Jian Chen, William Pruett, Robert Hester

We present HumMod Browser, a multi-scale exploratory visualization tool that allows physiologists to explore human physiology simulation data with more than 6000 attributes. We first present a tag cloud technique to reveal the significance of time-varying attributes and then study how a chain of tag clouds can form an exploratory visuailzation that assist multiple dataset comparison and query. One purpose is to reduce the high cognitive workload of understanding complex interactions within the large attribute space. The HumMod Browser produced can give physiologists flexible control over the visualization displayed for quick understanding of complicated simulation results. The visualization is constructed through the metaphorical bubble interface to allow dynamic view controls and the data relationships and context informaiton unfold as physiologists querying groups of connected bubbles within the hierarchical or causal relationships. HumMod Browser contributions to the interaction design and provides multi-scale coordinated interactive exploration for a new type of physiological modeling data. Two case studies have been reported with real datasets containing more than 6000 physiology attributes, which provide supportive evidence on the usefulness of HumMod Browser in supporting effective large-attribute-space exploration.