We geoscientists have a story to tell with our data, and every aspect... yes every aspect... of the visuals that help us communicate our findings is important.
From the type of graph or display we choose, to the tiny labels under our axes, whether our findings are influential and convincing depends on our displays. And let's be honest, a lot of us are in a scatterplot and line graph rut.
So, how do we branch out (or up, or down, depending on the data)? I have a few ideas I'll share over the coming weeks. Today, we will look at color and how it can impact our data displays—for those of us who can see it, and those of us who can't.
Sarah Compton
Editor, Enspired
Giving Your Data Some Color…
Maria Vonotna/Shutterstock.com
Geoscientists rely on communicating our data and results visually: graphs, maps, and pictures dominate our papers and presentations.
But... we’re not well-trained in the science and psychology behind the human eye-brain connection and how the colors in our display impact readers’ interpretations.
Why it matters: Ladies, we love our colors, and it’s probably because most of us can see them well. Worldwide, it’s estimated only .5 percent of women, but nearly 8 percent of men, are subject to a color vision deficiency (CVD).
Different types of CVDs impact the way an individual sees, or doesn’t see, colors.
Red-green CVDs include deuteranomaly and protanomaly. They dull green and red, respectively, and make them look like each other. As I’m looking at my daughter’s tomato plant to see which fruit to pick, I can only imagine the struggle.
Blue-yellow CVDs are tritanomaly and tritanopia. They cover a broader spectrum of color interference impacting blue and yellow.
While rarer, some people can’t see any color, which is called monochromacy or achromatopsia.
But also…The impact of color isn’t restricted to those with a CVD. The beloved rainbow color bar, for example, distorts the picture (pun intended 😉) by arbitrarily highlighting some differences while muting others.
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Let’s reclaim power over our displays—and their messages—by peeling ourselves away from our beloved rainbow color bars toward palettes that are more scientifically derived. How and why are they “more scientific”? Are they better? And if so, what makes them better?
I’m glad you asked…We know we can have datasets with different distributions, and a key to a good color selection is that the color bar should accurately reflect these basic data characteristics:
Continuous vs divergent. Some color bars are more suited to diverging data while others are better to show continuous data. We have an innate sense of what “order” colors should be, and the order should match the dataset we’re showing.
Brightness. Yellow is one of the brightest colors, and yet it can land in the middle of several color bars, even if we’re trying to show a continuous dataset. The same can be said for some of our “landscape” color bars like Vik (blue for low, brown for high…white in the middle? Why? WHY?).
Your mission—should you choose to accept it (and you should)—is to have color schemes with good perceptual order, meaning someone shouldn’t need to refer to the color bar to understand your display.
For example: Something like Batlow has white properly on the end, with blue/green on the opposite end and greys/browns in the middle. As someone who lives in the mountains and understands the relationship between tree line and snowline, I love this order for topography.
More to come. Though I covered mainly color bars this week, I want to expand on this concept of innovating in data displays and get us geoscientists out of our scatterplot and line graph ruts.
Remember, if you create a visual that requires explanation, or if you feel you have to preface your explanation with, “I know this is hard to read,” revamp your display! Someone should be able to understand it without the presentation.
Go deeper: There are several resources for such colormaps that came across my LinkedIn Feed this past week. They’re here, here, and in a nature paper about color use (or misuse) in science here.
Do you have your own neat tips and tricks for displaying data? Shoot me an email at editorial@aapg.org
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