This is a novel parallel coordinates design integrated with points (Scattering Points in Parallel Coordinates, SPPC), by taking advantage of both parallel coordinates and scatterplots. Two neighboring dimensions can be converted into a scatterplot directly, and multidimensional scaling is adopted to allow converting multiple axes into a single subplot. The transition between two visual types is designed in a seamless way. Uniform brushing functionality is implemented to allow the user to perform data selection on both points and parallel coordinate polylines without explicitly switching tools. A GPU accelerated Dimensional Incremental Multidimensional Scaling (DIMDS) has been developed to significantly improve the system performance.
We developed an approach of clustering data in parallel coordinates through interactive local operations, which allows users to directly apply attractive and repulsive operators at regions of interests. Taking advantages of an electricity interaction metaphor, our design enables users to interact directly with the parallel coordinate plots and provides great flexibility in exploring and revealing underlying patterns. With instant feedback, users are able to dynamically adjust the clustering parameters to reach an optimum. A graph indicating the logical relationship between clusters is also provided in our system.