I have measured out my life with coffee spoons…
—T.S. Eliot, The Love Song of J. Alfred Prufrock
Modern life in the Western world revolves around data that then becomes misinformation, disinformation, or, more rarely, information. In theory, we use this information to inform our decision-making process and then live fitter, happier lives. (Please hold all comments about how well the theory of Communism is working in the Soviet Union until the end.) However, for most of us, gleaning any kind of information from row after row after column after column of data is too laborious and too time consuming to be worth our time. And so most of us have turned to an emerging field that is known by many names but is perhaps best described as data visualisation.
Data can come in many different forms. It can be the gross domestic product of the United States. It can be the preferred term for carbonated beverages across the state of Pennsylvania. (Although I think we can all agree it is soda, not pop.) Data can be the route of Philadelphia’s regional rail lines. (And how late they happen to be on any given day.) Data can even be the price paid for a cup of tea in a bookstore.
And with all these different forms, one can have perhaps an even greater number of forms in which that data is visualised—either alone or in comparison to other datapoints. One can look at the GDP of the US as part of a bar chart against the GDPs of China and India. One can look at a map of Pennsylvania and see the barbaric lexicon near Pittsburgh in their preference for pop. One can look at a non-geographic map of SEPTA’s regional rail lines and all the stops of the Main Line. (And the lines coloured not by their destination but their on-time-ness.) One can even see the price of a cup of tea printed on a piece of paper in an itemised list. And each of those forms and the many, many others has inherent benefits and drawbacks. Each can be used appropriately. Or not. Some look good. Others not.
An interesting dividing line in this nascent field concerns the efficiency of any visualisation in communicating the data. Some statisticians argue for stripped down charts and tables with relatively little care put towards the aesthetics of the visualisation. On the other side, some designers care more for what many non-designers call the ‘prettification’ of data. That is to say, placing care towards the presentation and legibility of the visualisation perhaps at the expense of clearly communicating all the data. So where do I stand? Well damn it, Jim, I’m a designer, not a statistician. While I do believe in maintaining a level of fidelity to the data, that data must still be clearly communicated to reach the designated audience. The piece in question must still grab the attention of the audience enough to get them to delve into the layers of data.
The ultimate goal of this blog is to examine data visualisations, information graphics, charts, whatevers and break them down to see what may have been done well and not so well—all from my aforenoted perspective. Naturally, some may disagree and I wholly encourage dissent from the party line. My party line. If you find something interesting, please send it my way.
Modern life in the Western world revolves around data. Data that we create each and every day. We are aware of some of the data we create while we remain ignorant of some other data. We create it through every click of the mouse. Every swipe of a card. Every change of a channel. Every mobile phone dialed. Each and every day our lives are broken down into rows and columns. We may no longer measure our lives in coffee spoons, but we measure them nonetheless.