Tutorial 5
Integrating Visualization with Modeling and Simulation for Biomedical Applications (Half day) [proposal]
David Weinstein, University of Utah
Rob MacLeod, University of Utah
Marty Cole, University of Utah
Dana Brooks, Northeastern University
Chris Johnson, University of Utah
Robert McCarley, Harvard Medical School
Steven Parker, University of Utah
Craig Henriquez, Duke University

The traditional scientific computing pipeline is a non-integrated, batch mode, sequential process. The tools used for modeling the geometric domain of the problem are separate from the tools that approximate the governing equations and simulate the science, which in turn are separate from the tools used for visualizing and analyzing the results. Because the tools are separate, a significant amount of time is wasted saving temporary results, converting between file formats, moving data, and manually tracking various iterations. More importantly though, as the amount of time grows between when changes are made in the first stage (e.g., altering the geometric model) and the effects of those changes are seen in the last stage (e.g., changes to the streamlines), it becomes increasingly difficult to recognize and gain insights about the cause-effect relationship.

A far more efficient scenario is one in which the modeling, simulation, and visualization components are integrated into a single modular software architecture. In such a system, changes in one stage of the pipeline would immediately propagate to the other stages, allowing for the interactive investigation of many different parameters without the tools getting in the way. This what if? process is essential for iterative design, and is fundamental to scientific exploration, discovery, and analysis. It is precisely this vision that has driven the development of the Biomedical Problem Solving Environment, BioPSE. BioPSE is an open source software system that is currently being developed, distributed, and supported through the NIH NCRR Center for Bioelectric Field Modeling, Simulation, and Visualization, housed in the SCI Institute at the University of Utah.

In this course, we will begin by motivating the integration of modeling, simulation, and visualization tools into a common problem solving environment. We will describe the design of BioPSE, and will briefly review the underlying concepts of dataflow and computational steering. We will conclude the first portion of our course by demonstrating the BioPSE system, and providing an overview of the visualization capabilities of the system.

For the second part of the course, we will dive deeper into the functionality of BioPSE in the context of examining several real-world bioelectric field problems. Scientists currently using BioPSE to model, simulate, and visualize their data will describe both their driving application and how they are presently using BioPSE to investigate their research. Each speaker will conclude by presenting a demonstration of his application running in BioPSE.