Multidimensional Uncertainty Visualization with Parallel Coordinate and Star Glyph

Abstract

Prior work about uncertainty visualization has been primarily focused on spatio-temporal or univariate data. Little research has been reported on exploring uncertainty of multidimensional data. Therefore, improved visualizations applying to parallel coordinate and star glyph will be discussed and utilized to visualize multidimensional uncertainty. Firstly, parallel coordinate will be modified through imposing visual variables and expanding traditional two-dimensional visualization to three-dimensional way. Then the concept of multi-view visualizationwill be put forward,multidimensional uncertainty of data will be mapped by interactive integration of the visual representations of Parallel Coordinate and Star Glyph, which utilizes the advantages of both representations to offset the disadvantages they have separately to overcome the shortcoming that traditional parallel coordinate cannot map order of data and the problem of overlapping polylines. Meanwhile, four HCI technologies such as brushing, Linking, Zooming in/out, Hiding are imposed to the improved visualizations to help users to focus on what they find interesting and details of corresponding data with different uncertainty intervals. Eventually, MFC and OPENGL technology will be combined to construct an experimental platform to validate our proposed new ideas. Keyword: Uncertainty Visualization, Multidimensional Data, Parallel Coordinate, Star Glyph, HCI, MFC, OPENGL