Visually Enhanced Parallel Coordinates Plot With Two-Dimensional Kernel Density Scatter Plots

Abstract

Parallel coordinates plots are popular tools for high-dimensional data visualization. To alleviate the difficulties caused by the inherent defects that arise when the dimensions are increased, this study attached two-dimensional kernel density scatter plots to parallel coordinates plot, which integrates the Cartesian and parallel coordinate systems, to combine their benefits and conveniently explore the relationships between paired attributes. The collaborative design combining the two visual types was realized through the corelative axis swap interaction method, which allows users to freely exchange parallel coordinate axes while also updating the associated kernel density scatter plots based on the Cartesian coordinate system. In this study, we obtained six cases of real datasets and performed a field trial study to assess the usefulness of our method in assisting users in evaluating correlations between paired attributes. The results show that our method is more useful for analyzing the relationships between paired attributes.