Validation of SplitVector encoding and stereoscopy for quantitative visualization of quantum physics data in virtual environments

Abstract

We designed and evaluated SplitVector, a new vector field display approach to help scientists perform new discrimination tasks on scientific data shown in virtual environments (VEs). Our empirical study compared the SplitVector approach with three other approaches of direct linear representation, log, and text display common in information-rich VEs or IRVEs. Our results suggest the following: (1) SplitVectors improve the accuracy by about 10 times compared to the linear mapping and by 4 times to log in discrimination tasks; (2) SplitVectors lead to no significant differences from the IRVE text display approach, yet reduce the clutter; and (3) SplitVector improved task performance in both mono and stereoscopy conditions.