Gestaltlines

Abstract

We propose a general technique to visualize multivariate data sequences. It is based on a symbiotic combination of three powerful concepts from information visualization: sparklines, glyphs and gestalt theory. By visualizing several well-known data sets in new ways we first demonstrate how explicit consideration of gestalt principles can be used to leverage visual perception capabilities for the identification of patterns such as trends, periodicities, change points, or outliers. A more detailed case study with complex and noisy data from a psychological experiment then demonstrates how basic design ideas for gestaltlines can be applied in less controlled, and thus more realistic, situations. The case study is complemented with reports on feedback from domain experts and a user study, both indicating that gestaltlines can be a convenient and valid means to explore and communicate patterns in micro-visualizations.