Extensions of Parallel Coordinates for Interactive Exploration of Large Multi-Timepoint Data Sets

Parallel coordinate plots (PCPs) are commonly used in information visualization to provide insight into multi-variate data. These plots help to spot correlations between variables. PCPs have been successfully applied to unstructured datasets up to a few millions of points. In this paper, we present techniques to enhance the usability of PCPs for the exploration of large, multi-timepoint volumetric data sets, containing tens of millions of points per timestep. The main difficulties that arise when applying PCPs to large numbers of data points are visual clutter and slow performance, making interactive exploration infeasible. Moreover, the spatial context of the volumetric data is usually lost. We describe techniques for preprocessing using data quantization and compression, and for fast GPU-based rendering of PCPs using joint density distributions for each pair of consecutive variables, resulting in a smooth, continuous visualization. Also, fast brushing techniques are proposed for inte...

• Type: Conference
• Year: 2008
• Where: VIS
• Authors: Jorik Blaas, Charl P. Botha, Frits H. Post
• Keywords: Data Points, IEEE Visualization, Large Data Sets, VIS 2008, Visualization, Volumetric Data Sets