A lot of people who are new to data visualization feel that they have to design something novel and amazing in order for it to have impact. The field of data visualization is still quite young and evolving rapidly—and tools like the web and VR are continuing to expand the possibilities. So there is a lot of room for exploring new possibilities and creating new formats, as well as many examples of novel and amazing visualizations. And this should indeed inspire us as designers. But novelty is the icing, not the cake. It is not the core of a what makes a data visualization successful (or not).
Irene Ros, a colleague and friend and someone whom I admire very much, recently wrote a post about her own evolution as a designer, titled In Defense of Simplicity, A data Visualization Journey. In it, she describes how she came to a design philosophy anchored around usefulness:
Sure, it’s really wonderful to have recognition from my peers in the industry, but it’s actually even more wonderful to build a really simple tool for small clinic practitioners to track their patient experience data in a digital way for the first time; to show and explain to them a box plot and suddenly see them make use of it. A box plot is never going to win awards, but a well crafted tool that is simple to use is going to make someone’s life better, or at least a little easier.
I cannot second this statement any more strongly. A successful data visualization is one that communicates simply and well, so that the reader can make better decisions and take more useful actions. In order for this to happen, design needs to get out of the way.
Other designers have also touted the importance of keeping design spare in the service of usefulness. Edward Tufte, whom many consider the forefather of modern data visualization, famously coined the term chartjunk to refer to any line, color, or other element that does not directly contribute to the reader’s fundamental understanding of a graph. But designer Sha Hwang put it the most plainly: “Simplicity is clarity is kindness.”
In the quest for unique design, many new designers avoid visualization formats they find to be cliche or boring—bar charts and line graphs especially. But these formats are classics for a reason: they are highly effective! And because they are familiar, a lot of people can read them quickly.
Most of the time, making a reader decipher your new format or learn a new visual shorthand just slows them down, or even frustrates them to the point of walking away. It obfuscates the insight. Better to use a known format clearly and simply. It’s a bit like public speaking: if you stick to common vocabulary, your chance of being understood is much greater. You can stretch the audience by using a broad vocabulary if necessary or for interest, but you shouldn’t use a complicated word where a simpler one will do.
Sometimes, however, there really isn’t a “word” that means what you’re trying to convey, and you need to coin a new one. In these situations, a custom design may allow the data to become intuitive in a way that it couldn’t otherwise. My favorite classic example of this is the Periodic Table of the Elements: the physical shape of the table and the placement of each element, along with secondary signals such as color, reveal that certain characteristics of each element recur in regular intervals—periodically. But students often need to be taught how to read the table; it’s not as familiar or immediately accessible as a bar chart or line graph.
This is the trade-off of custom formats. What you gain in eventual insight and impact, you lose in the time it takes a reader to get to that insight, and possibly in attention and focus. Make that trade-off very carefully.
Your true goal should be to communicate with your reader and to give them that “aha!” moment of insight, not to impress them with your design skills. Good design is nearly unnoticeable, because it does not distract or call attention to itself.
And make no mistake: there is still plenty of room for good design within familiar formats. A great deal of skill and editing are required to make the supporting elements of a chart fade away and feel invisible, while allowing the data to shine. Think of it like the difference between a duck—appearing to float serenely on the water while paddling like mad underneath—and a dog, overeager and splashing everywhere.
The temptation to be the splashing dog is ubiquitous, even for experienced designers. In The Practical Guide to Information Design, Ronnie Lipton writes, “The quest for style, creativity, and peer awards often drives designers away from clarity, even when they know how to achieve it.” But resisting this temptation, and putting away your design ego in favor of serving the reader, is the right thing to do.
When the design gets out of the way of the data—when it serves and supports the data, rather than decorating it—insights can happen for the reader without their having to jump a lot of hurdle or perform extra mental work. Decisions can be made, actions taken. Instead of something amazing, you will have designed something useful. Clear. And kind.
Do you have thoughts on how to simplify data visualization? Share them in the comments.
Bio: Julie Steele is Director, Design at Silicon Valley data Science.
Original. Reposted with permission.
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