Person:

Cook, Matthew

Contemporary virtual reality systems enable academics to more efficiently explore and analyze complex three-dimensional (3D) content, but their utility is limited by visual short-term memory. Janus, a geometry agnostic shader script, circumvents this cognitive limitation by automatically rendering complex object meshes to fit entirely within the field-of-view of consumer head mounted displays. The resulting 360° vision experience represents an advantage over existing scientific data visualization tools, which have sought to replicate real-world viewing experiences but have inadvertently replicated associated limitations as well. By presenting data in such a way so as to effectively circumvent cognitive loads associated with body (or object) movement, academics can use the Janus shader to more readily engage in the exploratory analysis of complex 3D data sets, thereby facilitating scientific insight. This paper explores the motivations and design of the Janus shader, and describes preliminary results from user testing conducted under controlled conditions. For the 24 study participants (N=24), statistically significant time-to-completion decreases were observed for spatial analysis tasks taking place in intervention (Janus-enabled) VR scenes of low to moderate complexity.