On Twitter over the weekend, a number of visualisation grandees (Mortiz Stefaner, Andrew Vande Moere, Robert Kosara, Enrico Bertini and Noah Iliinsky) have been discussing and debating the rights and wrongs of a particularly unusual chloropleth map published in Good magazine.
Zoomable view here
Typically the infographics presented in Good magazine are inglorious pieces of graphic design being passed off as informative visualisation yet demonstrating very few of the principles that guide this subject area.
On this occasion, however, they have published a design (in collaboration with Gregory Hubacek) which demonstrates an innovative approach to representing three variables of data overlayed onto a geographical landscape. Whether this is the most effective method we’ll reserve judgment for now.
The data in question relates to the US Census American Community Survey and presents data for all US counties for high school graduates (%), college graduates (%) and median household income (£).
To present this data the designer has assigned a colour scheme to each variable (magenta for high school, yellow for college graduate and cyan for income) and then encoded the values for these variables on separate maps to show variation in the saturation of each colour.
To create the final design, he has then overlayed all three colour schemes onto a single map to represent the combined levels of high school graduates, college graduates and median income via a single colour which is a product of the original three. Imagine mixing different levels of blue, red and yellow paint on a palette. The legend below describes this in more graphic detail:
Initially, the result of this is a fairly unintuitive and difficult-to-read graphic. Each county’s colour needs translating backwards using the guide on the left to understand how it should be interpreted. It is, however, an unquestionably interesting approach to tackling the challenge of presenting three variables of data on a map. Furthermore, the difficulty in reading the colours does not imply that the design approach deceives the viewer. That is certainly not a criticism you could level at it.
The comments that have emerged about the design have raised concerns about the easy of perception of the colours and the extent of ‘learning’ required before being efficiently readable and have considered the idea of reducing the variables to from three to two by creating a combined ‘education’ variable from a merger of high-school and college graduates.
Further interesting narrative on this piece is available via Fastcodesign which talks about a method of interpretation where you try to consider the colour element missing more than the colour elements present to arrive some conclusion. The problem with this approach is that it only really works when you have particularly vivid and obvious colour combinations (such as orange meaning there is little blue, purple meaning there is little yellow etc.).
I really enjoy coming across new methods of visual display, especially when it is done in a considered manner like this rather than one purely designed to satisfy aesthetic appetites. The idea of encoding three sets of data using a RGB-mix is very novel. Unfortunately, I think the result is just too difficult to make sense of. Whilst our visual perception is excellent at detecting changes in a single colour, we simply aren’t built to easily detect this across three colour changes.
For what its worth, I think the suggestion to reduce the variables from three to two is an excellent suggestion, bring a better balance to the dataset and lowering the complexity factor. I then believe that taking the display away from a geographical platform and towards a scatter plot would be useful, perhaps colour coding specific region of the US to facilitate geographical conclusions. That display would present an effective visualisation response to the question/hypothesis being posed “are the richest Americans also the best educated?’.