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RESEARCH

A PERCEPTUALLY OPTIMISED BIVARIATE VISUALISATION SCHEME FOR HIGH-DIMENSIONAL FOLD-CHANGE DATA

[ARTICLE] This paper proposes and evaluates a comprehensible bivariate, perceptually optimized visualization scheme for high-dimensional data.

by Adalbert Wilhelm (ESSEC Business School), André MüllerLudwig LausserTimo Ropinski, Matthias Platzer, Heiko Neumann, Hans A. Kestler

Visualising data as diagrams using visual attributes such as colour, shape, size, and orientation is challenging. In particular, large data sets demand graphical display as an essential step in the analysis. In order to achieve comprehension often different attributes need to be displayed simultaneously. In this work a comprehensible bivariate, perceptually optimised visualisation scheme for high-dimensional data is proposed and evaluated. It can be used to show fold changes together with confidence values within a single diagram. The visualisation scheme consists of two parts: a uniform, symmetric, two-sided colour scale and a patch grid representation. Evaluation of uniformity and symmetry of the two-sided colour scale was performed in comparison to a standard RGB scale by twenty-five observers. Furthermore, the readability of the generated map was validated and compared to a bivariate heat map scheme.

[Please read the research paper here]

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