Authors: 
Sungahn Ko, Jieqiong Zhao, Jing Xia, Shehzad Afzal, Xiaoyu Wang, Greg Abram, Niklas Elmqvist, Len Kne, David Riper, Kelly Gaither, Shaun Kennedy, William Tolone, William Ribarsky, David Ebert
Keywords: 
Computational steering, visual analytics, critical infrastructure, homeland security.
Abstract: 
We present VASA, a visual analytics platform consisting of a \ desktop application, a component model, and a suite of distributed \ simulation components for modeling the impact of societal threats \ such as weather, food contamination, and traffic on critical \ infrastructure such as supply chains, road networks, and power \ grids. \ Each component encapsulates a high-fidelity simulation model that \ together form an asynchronous simulation pipeline: a system of \ systems of individual simulations with a common data and parameter \ exchange format. \ At the heart of VASA is the Workbench, a visual analytics \ application providing three distinct features: (1) low-fidelity \ approximations of the distributed simulation components using local \ simulation proxies to enable analysts to interactively configure a \ simulation run; (2) computational steering mechanisms to manage the \ execution of individual simulation components; and (3) \ spatiotemporal and interactive methods to explore the combined \ results of a simulation run. \ We showcase the utility of the platform using examples involving \ supply chains during a hurricane as well as food contamination in a \ fast food restaurant chain.
Conference presentation: