Parallel Box: Visually Comparable Representation for Multivariate Data Analysis

In visual analytics, data comparison is a means of analyzing data. We developed Parallel Box to support the visual analysis of multivariate data by facilitating the flexible comparison of numerous multivariate items. To compare the data distributions of multivariate data, we combine cumulative bar charts and box plots, tools that are widely used in statistics. Using shadow expression based on the visual Gestalt principles of grouping, Parallel Box enables a direct comparison between either datasets or variables. We performed a social media analysis as a case study of Parallel Box. The results of our analysis confirm that Parallel Box is useful for visual analysis.