It’s important to know about statistics and principles of data visualisation and presentation in order to assess the information that’s being presented to the you, the data consumer. It’s no accident that the English word ‘slogan’ comes from the Scottish Gaelic word sluagh-gairm or sluagh-ghairm (sluagh = “people” and gairm/ghairm = “call”, “proclamation”), roughly meaning ‘a call to the people’. In order to evaluate the reliability and subjectivity of the visualisation, it’s important to be able to critically assess evidence. The ability to read and understand the purpose of the presentations of data is an essential part of this process. This theme follows on from the BBC4 series ‘The Joy of Stats’, which I’ve eagerly awaited for some time; if you haven’t seen it, here is the link to the BBC website.
There are many beautiful data illustrations, and to evaluate them properly, it’s important to look at the purpose of the illustration. There are approximately two main threads of displaying data: Data Visualisation and Infographics.
Data Visualisation provides ways of analysing large amounts of data, which allows the data consumer to draw their own conclusions. Believe it or not, Data Visualisation impinges on our everyday life. Our bank statements, pension statements, and mobile phone bills are examples of presented data that we receive frequently. Very often, the data is not static in nature, but fluid and dynamic.
Infographics is focused on clarification; taking existing data, and re-packaging it so that it is easier for consumers to assimilate the information. Intellectual and artistic beauty, which focuses simplifying difficult concepts. It can help to express profound ideas in ways that are very creative. These visualisations tend to be static, with limited interaction.
Data Visualisation is about storytelling – going from the data to the facts. Data Visualisation can be used in different ways. In the book The Little Book of Shocking Global Facts by Barnbrook Designs, the data is displayed in a manner which is subjective rather than following principles of data display. Adherents of Tufte’s design principles may well be taken aback by the following display, which is taken from Creative Design:
Fans of Edward Tufte and Stephen Few may well point out the following issues with this visualisation:
It’s a pie chart. Enough said.
The ‘fill’ is confusing and is perhaps giving the viewer a headache due to the Hermann illusion.
The legend is too small and it’s difficult to match the values with the actual content of the pie chart.
The greyscale isn’t easy to distinguish perceptually. As Colin Ware points out in his assessment of pre-attentive attributes, it is expected that brighter or darker colours = greater values, but, in this case, there is no relationship between value and intensity.
In defence of this visualisation, the impact isn’t in the ‘rightness’ or ‘wrongness’ of the visualisation since this is a battlecry about the unfairness of financial control being in the hands of the few. In order for the visualisation to meet its purpose, it is a subjective presentation of the data which doesn’t stick to data visualisation principles for the purpose of raising a battle-cry about financial control, and ultimately, power. A knowledge of statistics, and data visualisation, can help the data consumer to assess the image, and to evaluate how much subjectivity is involved. Thus, this is the interpretative element which is involved in Data Visualisation. There are plenty of examples around on the Internet, and here are some examples, using Tableau, from my own blog. I also like work produced by the following tweeps: Freakalytics, Andy Cotgreave or you could head over to the Tableau Public site and have a look.
On the other hand, Infographics sets out to simplify the message on behalf of the data consumer. Unlike data visualisation, there are no real ‘rules’ around presentation since this would go against the grain of the creative process of producing an innovative infographic. This is where I get excited since it gives me the opportunity to show off some of my favourites here:
I also like Information is Beautiful by David McCandless.
To summarise, it’s important to understand the aim of the visualisation being displayed. Broadly speaking, if it’s recycling the data to simplify the message for you, then its Infographics. If it is presenting you with the data to help you make your own mind up, then it’s Data Visualisation. Often the boundaries are not clear; that’s where a knowledge of statistics is essential, in order to try and evaluate the subjectivity of the message, and to help the data consumer to find alternative interpretations.
I will be interested to hear your thoughts!