Progressive Visual Analytics Using Scagnostics and an Automatic Partitioning Variables Selection Method

DongHwa Shin, Sehi L’Yi, Hyunjoo Song, Jinwook Seo

http://doi.org/10.5626/JOK.2018.45.8.801

In this paper, we propose a visual analytics system that combines progressive visualization with a partitioning variables selection method, one of the analytic techniques based on a scagnostics concept. In order to overcome the problems of scalability and performance associated with the existing method, all of the interface elements are designed so as to update the analysis progress in real time. The interface consists of two parts: an overview of the scatterplots to be analyzed and a detailed view for exploring interesting scatterplots in detail. We introduce the design rationale of our system and present a data analysis scenario to show how users can effectively use the system.