The misuse of colour in science communication

Abstract

The accurate representation of data is essential in science communication. However, colour maps that visually distort data through uneven colour gradients or are unreadable to those with colour-vision deficiency remain prevalent in science. These include, but are not limited to, rainbow-like and red–green colour maps. Here, we present a simple guide for the scientific use of colour. We show how scientifically derived colour maps report true data variations, reduce complexity, and are accessible for people with colour-vision deficiencies. We highlight ways for the scientific community to identify and prevent the misuse of colour in science, and call for a proactive step away from colour misuse among the community, publishers, and the press.

Raman and Photoluminescence Mapping of Gem Materials

“…Depending on the limits chosen, the range of data can be perceived very differently by the reader (compare Figure 3C, right with Figure 3D). Additionally, the rainbow color palette is commonly used in many software programs (including the one accompanying the OMNICxi used in these studies), but it can be problematic as the information can be perceived quite differently if reproduced in gray-scale or observed by individuals with color vision deficiencies [18]. With that in mind, we have modified the color palette used in these Raman/PL maps to account for such issues facing false color maps.…”

Rainbow colors distort and mislead research in hydrology – guidance for better visualizations and science communication

“…When that is the case, there are several techniques how color can be used in an accessible way. Crameri et al (2020) presented a thoughtful decision tree explaining how color depending on data types should be used in visualizations. They differentiated between the direction of color gradients to encode higher or lower values according to the chosen background color (light or dark).…”

“…This affects all people, even those with normal color vision. The same Euclidean distances in mapping or the same data ranges in continuous or binned variables are not equally represented by a rainbow color map (Crameri et al, 2020;Sharma and Trussell, 1997). Especially for data comparisons over a wider distance in the color map the distorted colors of the rainbow impedes reliable judgements (Liu and Heer, 2018).…”

“…The color map distorts the data representation if the change in value is not visually commensurate with the change in color (Wong, 2010(Wong, , 2011b. Discordant false coloring may lead to visual errors up to 7.5% of the total displayed data variation (Crameri et al, 2020). For example, research has also shown that replacing a rainbow color map with a perceptual uniform color map could identify hidden structures in mapping (Rogowitz et al, 1996).…”

“…A thoughtful and scientifically correct color map should allow for all types of dichromatic views (i.e., color vision deficiency) and unambiguous perception of the displayed data. As it is now scientific standard and best practice to avoid any rainbow or rainbow-derivates color map (Crameri et al, 2020) we want to challenge the use of rainbow color maps in hydrological science by analyzing the status quo of rainbow visualizations in hydrological and environmental publications. In this study we evaluate the use of rainbow and red-green color use in the journal Hydrology and Earth System Sciences (HESS) in preprints and publications in 2020 and their use over time (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020).…”