You’ve probably heard the sayings “All style but no substance”, “the wheel is spinning but the hamster’s dead” and we've all encountered people who look beautiful but don't contain much else, but what about data visualizations and dashboards?
It is very easy to get wrapped up in the idea that dashboards and other data visualizations need to pretty and fancy in order to be interesting. Unfortunately the main aspect of data visualization tends to get lost when doing so – accurately representing data in a form most easily consumable by the viewer.
Brett Keller recently posted on this subject on his blog. Keller points out an infographic from the blog Information is Beautiful (David McCandless).
Keller states “The problem is that I don’t think raw numbers of deaths tell us very much, and can actually be quite misleading. Someone who saw only this infographic might well end up less well-informed than if they didn’t see it. Looking at the red circles you get the impression that non-communicable and infectious diseases were roughly equivalent in importance in the 20th century, followed by “humanity” (war, murder, etc) and cancer.
The root problem is that mortality is inevitable for everyone, everywhere. This graphic lumps together pneumonia deaths at age 1 with car accidents at age 20, and cancer deaths at 50 with heart disease deaths at 80. We typically don’t (and I would argue should’t (sic)) assign the same weight to a death in childhood or the prime of life with one that comes at the end of a long, satisfying life”
Keller is correct. Also the visualization itself – using circles and the use of color – leaves much to be desired.
Cardiovascular Disease has more deaths associated with it than Humanity and Cancer, yet appears less important due to the use of color. The color in this infographic denotes category class and Carviovascular Disease is a subcategory of Non-communicable Diseases.
The circles themselves are difficult to compare because our brain’s ability to recognize spatial area isn’t as developed as our ability to recognize differences in length (using a stacked bar chart for example).
Another visualization that people swooned over circulated around the 2012 summer Olympics. While the concept is interesting and beautiful, the actual visuals fail to really tell us anything. There are no labels to inform the viewer what color corresponds to what continental region and there are no numbers provided to give us a sense of scale.
In “% of Worldwide Coca-Cola Sales” I think the red one may be 50%? Who knows? Again, our brain’s ability to recognize spatial area isn’t the best, especially when trying to assign it to a number.
A friend once said dashboards and data visualizations are now going through the same thing that powerpoint did in the 90s. Remember those flashy monstrosities that we incredibly over designed? You wanted to use every effect (visual or sound) possible vs. today’s simplistic design approach?
3D is a prime example of this “powerpoint effect” on data visualization. While 3 dimensional images seem cool, it’s actually harder to read differences than when the same data is presented in 2 dimensions.
The whole point of data visualization is to present information to people so that it’s easier for them to consume, spot trends, and understand the data story. 3D requires the viewer to spend more time trying to understand the data being presented to them than necessary.
Good data visualizations can be both beautiful and informative and beauty can come in the form of simplistic design. We also need to shift our understanding of what beautiful data visualizations are. Recognize that true beauty comes from the ability to understand the data story as easily as possible, rather than relying on flashy lights and gimmicks.