Sex, Lives and Red Tape

Visualising Data (Guardian Masterclass notes)

On Sunday 19th October I went along to the “Introduction to infographics and data visualisation” (Guardian Masterclass). The main aim was to explore different approaches to communicating complex data to a range of audiences. For example, as a researcher I hope to eventually publish my analysis in a peer-review journal to share my findings with an academic audience. However, of equal importance is to communicate these findings to a more general audience, and I think infographics are a great mean to that end. The day turned out to be a great, informative, with a good balance of theory and practical advice.

Why visualise data?

As humans, as are primarily visual creatures. Visual instructions make us 3 times more likely to complete a task, compared to written instructions alone. (For example, imagine trying to assemble Ikea flat pack furniture reading only text versus the pictures, arrows and diagrams). The combination of images (which provide an immediate emotional impact) combined with insight and information through text, help us to learn. As such, data visualisation is a form of storytelling.

billionThe main ‘schools of thought’ in visualising data are Tufte and McCandless. The Tufte approach is best when your audience is technical or expert, and this approach prioritises data quality over design. In a sense, every pixel should correspond to something in the dataset, otherwise it is just chart junk. McCandless on the other hand prioritises getting the maximum number of people interested in the data, who would previously not have been interested. Therefore for McCandless design is king, and slight data rounding/manipulation is ok if it helps to get the main message across.

A good example is this famous infographic “Billion Dollar O Gram” by McCandless (click to enlarge). The actual data almost certainly doesn’t fit into such nice linear boxes. In fact, at the bottom is a note “some slight visual cheating to make things fit”. I imagine this would be deemed entirely inappropriate by Tufte followers. However the key question to deciding upon your approach (Tufte v McCanless) will be: who is your audience?

How to develop an infographic

We were introduced to a fool-proof process which (apparently) works no matter what the project, story or client. I say apparently, as I haven’t put it to the test as yet, but it does intuitively make a lot of sense. The process involves 4 steps, which must be followed in a consecutive order.


  1. Data. The data ALWAYS comes first. And, similar to any other research the quality and robustness of the data affect the final product (“garbage in, garbage out”).
  2. Story.  What are the key messages within the data which which will interest the audience? The story is the connection with the audience, and as with most good stories should have a beginning, middle and an end.
  3. Chart. Line and bar charts are the most popular types and tend to be considered most ‘scientific’ of outputs. However what charting should be used ought to depend upon when is needed to bring your story to life. The aim of the chart is to speed up understanding. *This, from what I gathered, is where knowledge of the range of software and tools comes in handy, and probably is the area of greatest learning on my part – lots of homework to do here…
  4. Design. The aesthetic part of the process – making the product look good. If it looks good, this will get your foot in the door. If your story is good, that will keep people there. So design encompasses choice of font, colour, layout…etc form, elegance and beauty is required to appeal to the eye.

Other hints and tips

Collaboration and teamwork are important. The ‘masters’ noted how you are unlikely to find someone with the whole skill-set, and the best work tends to be the product of a team effort. (Although it can be useful to expand your skills to learn and appreciate different parts of the process).

Remember the rule of 7. (Or as I remember it from my undergrad classes 7+/-2.) In the 1950s George A Millar reported that 7 is the optimal number for human memory,  afterwhich information overload tends to occur.

Another master highlighted that society is increasingly being bombarded with volumes of data  and we have an increasing demand for information. However, low levels of statistical literacy in general population is often a barrier to good decisions. Therefore although aesthetics are appealing, the outcome of informing decision making (and therefore enhancing understanding) should not be forgotten.

It can be helpful to think about the characteristics you wish to expose in your data visualisation. E.g. correlation, change overtime, magnitude, distribution, ranking, uncertainty, deviation, spatial, part to whole… etc this fits in with the story building part of the process.

How to make it all beautiful…  the job of design is form and function combined. If you fail to communicate, you fail to design. The job is visual story telling. The final product should have visual clarity and visual persuasion (Scott McClough).

Further info / resources to explore:


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This entry was posted on October 23, 2014 by in Communicating public health and tagged , .