SBIR/STTR Award attributes
Analysis of high-dimensional, cross-domain, heterogeneous battlespace data generates significant cognitive burden on users. Collaboration over a shared dataset can also cause cognitive burden as multiple users do not always have the same experience level for making sense of the displayed information. Next generation hardware and software can reduce the cognitive burden present in data-analysis via natural 3D information visualization. FoVI3Ds proposed Predictive Visualization to Aid Rapid Decision-Making effort is to develop a methodology for visualizing battlespace data within a heterogeneous user-centric display environment where multiple display architectures can be employed for collaboration and decision making simultaneously FoVI3Ds effort will:Design methodology for visualizing descriptive aspects within a heterogeneous display ecosystem that allows intuitive human-computer interaction within each display environment (2D, 2.5D, 3D).Expand on RM-Vis by focusing on user-centricity and Visualization Approaches in Natural 3D.Develop visualizations for descriptive aspects like location, status, capability, type, environment, novel iconography, and data-vis overlays such as course of action and radar coverage ranges. New classes of display technology enhance spatial understanding by presenting natural 3D visualsincluding VR goggles and emerging, glasses-free light-field displays. FoVI3Ds approach supports all display types and provides a publish/subscribe model to allow multiple user
