Data Designer


The Message

The "message" or the "story" of an infographic is an often hotly debated topic in the world of information design. There are those who believe every chart should tell a story, and then there are those who are strictly against the idea of defining a narrative for the audience. I can certainly see the value in both, the former can guide the viewer through a complex set of data by highlighting key points, and the latter allows freer exploration. Both sides however will no doubt agree that no matter what form the message takes, the data always comes first.  

Putting the Blinkers On

But what about starting with the message first and working backwards? One designer interviewed over on Visual Loop discusses his method for creating infographics:

The new way... puts the message first and completely inverts the process of creating an infographic. It’s the ‘message’ that decides the presentation. The numbers, visual or text or a combination of these are to only support the way of putting the message across. This also changes the way one conceptualises a graphic.

The thought starts with the message and then gets into putting other related information together to support it instead of starting with the data and thinking of what to make of it – the message. The advantage of taking this route is also that you are not just restricted by topics or numbers or just presenting ‘news’. You can go a step further and air your ‘views’ too to make a point.
— Raj Kamal

A worrisome thought process indeed. Putting the blinkers on and and only finding evidence to support your predefined message or narrative is a sure-fire way to completely mislead your audience (even if you have good intentions). 

Helpfully Misleading

Take this wonderful example from io9. If my predefined message or hypothesis was that "an increase in organic food sales causes autism" I could very much create a chart that appeared to show this. Now nothing on the chart below is technically incorrect, indeed, both organic food sales and cases of autism have increased over the past decade but correlation and proximity should not necessarily imply causation.

Yet by cherry-picking data and presenting it in this way I can illustrate my intended message to an audience and as if by magic I appear to have proven my own hypothesis. As io9 puts it: 

The chart is nonetheless a simple and compelling example of how susceptible we can be to logical fallacies, cognitive biases, and extracting what we believe to be meaningful information from insignificant or coincidental data.


It's very easy as an information designer to mislead the audience via visual means, and there unfortunately is a startling number of examples out there (I'm looking at you Fox News).

By starting with a predetermined hypothesis, you're misleading your audience, whether intentionally or not. Infographics should be about conveying the truth and finding the meaning within a set of data, and not about picking and choosing the data that simply supports your message or claim. I'm all for using data from different sources and combining them into one graphic to build up a narrative, to provide some back story and additional context. It's dishonest however, to leave out those pieces of data that don't quite fit with your intended message. Unfortunately this cherry-picking is all too common.  

I'll sign off with Alberto Cairo's thoughts on the matter:

Infographics designers shouldn’t act as marketing drones or blindfolded activists. They need to bring science, maths, and logic to their thinking process. No exceptions.

What Kamal’s article promotes is an infographics philosophy dominated by pretty pictures based on scant data, messages backed by spotty evidence, hollow displays of visual “creativity” that can be profoundly dishonest. This is a philosophy in which coming up with a good “concept” is more important than being truthful and thorough. Unfortunately, no amount of visual fluff will ever make up for a deep lack of substance