Round pegs and square holes

Circular forms have become a very fashionable method in an attempt to visually communicate data. Their popularity is somewhat perplexing given the additional challenges they present to both the designer and user, but it seams we just can’t get enough of them. Neither clarity nor efficiency appear to be issues of major concern when these forms are used, however perhaps that is where the secret to their success lies.

Olympic Evolution, Alicia Korn

I came across this piece by Alicia Korn a few months ago and was inspired to create an Olympic graphic of my own. Olympic Evolution displays the competing counties over the years. We immediately get a sense of enormous growth in participants from 1896 to 2008, and the absence of the event during the wars is stark, but some of the finer details become obscured by those curves. Looking at this we may assume that the number competing in the last four events has decreased slightly year-on-year, although without counting I expect this is quite the opposite and this illusion is due to the longer circumference of the outer most circles. Having the counties scattered like this makes it challenging to spot any abnormalities, for example can you identify the year the United States did not attend from the graphic alone? All the necessary information is present, but it is not ordered in a way we can process efficiently. The viewer is unquestionably challenged, but maybe that is why I feel so intrigued by it and ultimately rewarded once I have invested a little time. My favorite visualisations are those which immediately grab our attention and sustain our interest over time, and for me this wins on both counts.

When it came to creating my own Olympic visualisation, using data on gold medals won by nation and sport, I wanted to combine engaging visuals with deeper analytics, and not for the first time I decided to split the task in two by first providing an overview, followed by an opportunity to take a more in-depth look and discover the stories within the data. The circular section at the top will hopefully act as the bait, encouraging viewers to come closer and get a general sense of the scale of the data involved. The grids below are designed with clarity and efficiency in mind and should satisfy those who wish to drill down deeper. See the finished piece >here.

Gold, Ben Willers

Does it succeed? How could it be improved? As ever I am eager to hear any thoughts.

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For further reading see my dissertation on area encoding >here.