Experiments in Immersive Virtual Reality for Scientific Visualization

This article provides a snapshot of immersive virtual reality (IVR) use for scientific visualization, in the context of the evolution of computing in general and of user interfaces in particular. The main thesis of this article is that IVR has great potential for dealing with the serious problem of exponentially growing scientific datasets. Our ability to produce large datasets both through numerical simulation and through data acquisition via sensors is outrunning our ability to make sense of those datasets. While our idea of “large” datasets used to be measured in hundreds of gigabytes, based at least in part on what we could easily store, manipulate, and display in real time, today's science and engineering are producing terabytes and soon even petabytes, both from observation via sensors and as output from numerical simulation. Clearly, visualization by itself will not solve the problem of understanding truly large datasets that would overwhelm both display capacity and the human visual system. We advocate a human–computer partnership that draws on the strengths of each partner, with algorithmic culling and feature-detection used to identify the small fraction of the data that should be visually examined in detail by the human. Our hope is that IVR will be a potent tool to let humans “see” patterns, trends, and anomalies in their data well beyond what they can do with conventional 3D desktop displays.