Parallel Assemblies Plot, a visualization tool to explore categorical and quantitative data: application to digital mobility outcomes

This paper presents a tool enabling the visual analysis of multivariate heterogeneous data. Large amounts of measured and contextual data are being gathered for a large number of applications, increasing connectivity across different data types. While measured data are often quantitative, contextual data tend to be categorical. This results in datasets containing multivariate data with heterogeneous properties. Difference in the natures of these properties raises challenges when combining them for analysis. This paper presents the design of a tool that enables the exploration of multivariate heterogeneous data by combining the strengths of Parallel Coordinates and Parallel Sets. The design relied on the application domain of real-life mobility monitoring that is particularly affected by the challenge mentioned above. To validate the suggested approach this paper presents the result of a usability evaluation, which confirms that the presented design is as efficient as other exiting tools while providing more features for correlation analysis.