A perceptually optimised bivariate visualisation scheme for high-dimensional fold-change data

André Müller, Ludwig Lausser, Adalbert Wilhelm, Timo Ropinski, Matthias Platzer, Heiko Neumann () and Hans A. Kestler ()
Additional contact information
André Müller: Ulm University
Ludwig Lausser: Ulm University
Adalbert Wilhelm: Jacobs University
Timo Ropinski: Ulm University
Matthias Platzer: Fritz Lipmann Institut
Heiko Neumann: Ulm University
Hans A. Kestler: Ulm University

Advances in Data Analysis and Classification, 2021, vol. 15, issue 2, No 9, 463-480

Abstract: Abstract 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.

Keywords: Colour scales; Bivariate; Visualisation; 92-04; 62H35; 62P10; 92C42 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11634-020-00416-5

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