, Henan Zhao, , , Jian Chen
We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display the digit and the exponent of a numerical value separately, thus improving legibility by bounding the visualized vector length regardless of vector magnitude. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in information-rich virtual environments. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by 4 times to log in discrimination tasks; (2) SplitVectors lead to no significant differences from the textual display approach, without cluttering the scene; (3) SplitVectors and text are less sensitive to data scale than linear and logarithmic approaches; (4) using log can be problematic as participants' confidence was as high as directly reading from the text, but their accuracy was poor; (5) Stereoscopy improved performance, especially in more challenging discrimination tasks. Because data with large ranges of magnitude are omnipresent in physics simulations and many other flow and tensor field analysis and because design methods that work for both mono and stereo conditions are important, we discuss the potential uses of our new design in visualization.
IEEE Transactions on Visualization and Computer Graphics
Vector field, scientific visualization in virtual environments, quantum physics, visual encoding, large-range data