Stop using 'rainbow' maps - it doesn't do you data justice
The choice of color to represent information in scientific images is a fundamental part of communicating results. However, there are several color palettes that are widely used to display compelling scientific results that are not only deceptively dangerous, but also unreadable by a portion of the population.
For decades, scientists have been pushing for lasting change to remove these palettes from public consumption, but the battle for universal access in science communication is ongoing.
A color map is a palette of different colors that assign values to regions on a plot. An example of a map is a deceptive color rainbow, which usually starts with blue for low values, then goes through cyan, green, yellow, orange, and finally red for high values. This color combination is no different, allowing us to see a visual view of medium value, or series, that would make organizational values from low to high intuitive.
Color brings life to data
Using color bar graphs scientists can transform the data they have collected into something meaningful to be widely shared. This could be just a first impression of a black hole, the mapping of votes cast in political elections, the planning of an expensive rover route on the Martian landscape, critical communication about climate change or a critical diagnosis of heart disease.
Despite the clarity of color, scientists often choose the basic setting of visual software used.
Rainbow - no jet - color palettes are often the default setting for software, but the beautiful hue of blue to red is deceptive when displaying scientific data.
Basically, the transition between the colors in the palette is not smooth. For example, the transition between blue and green and then between yellow and red occurs over a short distance. Bay and batlow, are examples of even color palettes, where the colors change smoothly over the color bar.
To put this in context, a palette that alternates between colors is wild as if the position of x or y axis with numbers that are not evenly spaced. In jet color maps, this would equate to numbers one to four being close together and eight to 10 far apart. Such an uneven color gradient means that some parts of the palette would be naturally marked over others, moving the data. RGB color ranges are based on which such uneven color gradients are created mathematically simply, but not by how we see colors and see the differences between them.
Another issue with uneven color palette as rainbow is that data presented using these colors may be illegible or inaccurate for visually impaired or color blind persons. Color maps that incorporate both red and green colors with equal light cannot be read by a large fraction of the population.
The general estimate is that 0.5 percent of women and eight percent of men worldwide are subject to a lack of color vision. Although these numbers are lower and are almost disappearing in numbers from sub-Saharan Africa, they appear to be much higher in numbers with a larger fraction of white people. as, for example, in Scandinavia.
Needless to say, scientific results should be visible to so many people, and these shortcomings in color vision should be taken into account.
The winding road to the end of the rainbow
The issues with jet, rainbow and other non-linear color palettes have been known for years. While some areas of science have made significant changes to color policy best practices, others have adhered to their basic preferences.
As researchers interested in more effective data communication, we will explain techniques scientists can use to communicate their results more effectively: avoid using jet no rainbow custom color palettes; if red and green need to be used, make sure they are not the same brightness for accessibility; and use a palette that alternates between colors.
The challenges associated with rainbow palettes are increasingly recognized. Some academic publications - such as Geology of nature - Adopted a fairer color palette policy for new applications. The Intergovernmental Panel on Climate Change has figure-friendly guidance.
Software packages such as MATLAB and Python have been removed rainbow as their default color palette for data view features. However, old habits are dying hard and vigilance is still needed - it's important to rule out bad color choices when noticed (otherwise the movements will be repeated).
Better scientific communication, better results
The importance of properly sharing scientific data in an accessible way cannot be overstated. Uneven color gradients are often chosen to emphasize potential danger zones, such as hurricane-bounding boundaries or the normal spread of the virus.
Unbalancedly represented data-based decisions could yield results, for example, a Martian rover being deployed over land that is too steep as the terrain has been see erroneously, or a medical worker makes an erroneous diagnosis based on uneven color gradients.
Accessible science for all begins with a move away from shortcomings. This can start with students learning even to choose color levels for term projects, to international publishers rejecting papers for false figures. One day, it could even be the introduction of the Canadian Weather Service moving away from dramatic uneven palettes to mark climate changes.
Basically, using an accurate color map is tantamount to misleading the public by moving data, and this has a huge impact.
Article by Philip Heron, Associate Professor, Environmental Geology, University of Toronto; Fabio Crameri, Researcher in Geology, University of Oslo, and Grace Shephard, Researcher, Geology and Geophysics, University of Oslo
This article is republished from The Conversation under a Creative Commons license. Read the original article.