Raphaël Tuor
Denis Lalanne
ABSTRACT
In this article we discuss the techniques available to represent categorical data in Parallel Coordinates, a widely used visualisation method for multivariate datasets analysis tasks. We propose Parallel Bubbles, a frequency-based method improving the graphical perception of categorical dimensions in Parallel Coordinates plots. We compare the performance of three variations of Parallel Coordinates in a user study, with similarity and frequency tasks. Parallel Bubbles are a good tradeoff in terms of performance for both types of tasks, and adding a visual encoding causes a significative difference in performance. This study is the first of a series of papers which will aim at testing the three visualisation methods in tasks centered on the numerical axis, and where Parallel Sets performance will probably be worse.
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