, , , Jian Chen, Henan Zhao
We designed and evaluated SplitVector, a new vector field display approach to enable scientists to perform new discrimination tasks related to showing scientific data in virtual environments (VEs). Our SplitVector design is motivated by the challenges of performing discrimination tasks (e.g., numerical readings and ratio tasks), for real-world large dynamic range data in quantum physics simulations. SplitVector uses scientific notation to display the coefficient and the power separately, to improve reading and legibility as it bounds the visualized vector length regardless of vector magnitude. We present an empirical study to compare four approaches: direct linear representation, log, SplitVector, and text display in information-rich VEs or IRVEs, for 20 participants to perform three domain analyses tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger one between two vectors (a detection task). Participants used both mono and stereo conditions. Our results suggested the following (1) SplitVectors improved the accuracy by about 10 times compared to the conventional linear mapping and by 4 times to the log approach in discrimination tasks; (2) SplitVectors led to no significant differences from the IRVE text display approach, yet reduced the clutter; (3) SplitVectors and text were less sensitive to data scale than linear and log and can work well for data at any scale; and (4) using log with cautious as participants' confidences were as high as directly reading from the text, despite accuracy was rather poor. Because data with a large range of magnitude is omnipresent in physics simulations and many other flow and tensor field analyses in VEs and because design methods working for both mono and stereo conditions are important, we discuss the potential uses of our new design in scientific visualization in VEs.
Special issue of IEEE Transactions on Visualization and Computer Graphics (TVCG)
March 23-27, 2015
IEEE VR 2015
Vector ¿eld, scienti¿c visualization in virtual environments, quantum physics, visual encoding, large dynamic range data