Modeling the real world ain’t easy

“Illustrations and graphics should be as smarts as the worlds in the newspaper.” (Edward Tufte)

When I tell people my thesis is about the evolution of morality they usually blink. Some ask for clarification, others joke, and most are eager to engage in a philosophical discussion. But absolutely no one assumes I’m basing my experiments on real people.

Data journalists aren’t so fortunate however. They report current events, and as such any piece of visualization they use has to represent the truth. Virtually no one realizes that a representation of the world is just that… a representation. It is just as much a model of the world as the one I use to test an obscure theory. But the context of journalism changes the audience’s perception, and thus their expectations. A good data journalist is aware of these expectations and keeps them in mind when choosing which visuals to accompany her story.

In his lecture on the main principles of datavisualization, Alberto Cairo gives two definitions for visualizations:
1. A graphical representation of evidence.
2. A tool for analysis, communication, and understanding.

Both stress the fact that visualizations are tools, to be used to better explain the data than mere words are capable of. It is a wonderful tool for sure, one with the potential to reach out across language barriers and show audience a pattern they otherwise might never have been aware of. However, like any tool, it should be treated with care and respect.

“Charts, graphs, maps, and diagrams don’t lie. People who design graphics do.” (Alberto Cairo)

It is very easy to tell a completely different story using the exact same data but two different graphs. Below is an example from… which graph  shows the greatest increase?


The answer is of course, neither… but because the right one’s Y-axe starts at 48%, the impression is given that the data to the right is far more volatile.

When you look at these graphs side by side in the context in this blog, the difference is easy to pick up. But as I have mentioned in previous blogs… usually the audience doesn’t have the time or energy to study these things in detail.  And those that do have the time, tend to notice these things and publish them. It is therefore the journalist’s responsibility to ensure that graphs and other forms of visualization are always correct. Not only to protect one’s audience from drawing the wrong conclusion, but also to protect your reputation as a journalist.Fortunately, there are many tips out there on how to avoid these mishaps.

“Three rules to keep in mind (when choosing your graphics form)” (Alberto Cairo)

  1. Think about the audience and the publication.
  2. Think of the questions your graphic should help answer.
  3. Can you understand the graphic without reading every single number?

Think about the audience and the publication.

If you are a data journalist, chances are that your audience is highly interested in data processing, visualizations and the subject matter itself. As such, they will notice when you present a misleading visualization and they won’t be shy to tell others about it. Do not insult your audience. 

Think of the questions your graphic should help answer.

What will your audience do with this information? Will they share it with others? Will they try to see if it matches their own data on the subject? Or will they simply glance at it and either accept or reject it, based on their existing world views? And is that what you would want them to do with it? Cairo’s advice is to make a list of these questions and use that as a guideline to decide which graph to use. The Graphic Cheat Sheet is a great help for that.

Can you understand the graphic without reading every single number?

The right graph in the example above clearly fails this last test, as it can only be read correctly if the reader looks at the numbers. Of course, exposition is at times necessary, but it’s best to put that part in words, either in the main text or as an explanation near the graph itself. An example was made during this week’s class presentations, when mapping a warzone area turned out to be very difficult due to the constantly changing situation. It was therefore suggested that readers be told that this map was made at a given time at a given date, and would be frequently updated. Personally, I agree with that idea… better to acknowledge your limits than to pretend and be caught.

Do not insult your audience, they know your world ain’t real.

They say the first step in recovery is accepting you have a problem. Data journalists need to accept that visualizations have a big problem: they are open to abuse. It is therefore important to accept that whenever you attempt to visualize your data, you ask Cairo’s three questions and use the cheat sheet to choose the appropriate format. And when you come across any limits to your chosen form… acknowledge them openly on your site, so that they themselves may become aware of these limitations. Who knows, one of them might come up with a solution.


3 thoughts on “Modeling the real world ain’t easy

  1. Same as you, I fully agree with Alberto Cairo’s three rules. The visualization challenges the journalists’ design skills and more knowledge besides their storytelling. In the past, narrative styles contribute a lot to a good story, whereas nowadays an attractive news starts with an interesting graph. Our audiences know far more than we think, and usually a journalist’s credibility is questioned by a detailed and tiny error. As you said, accepting the limitation and be open to the crowd, that would be a good solution. I noticed here you mentioned the wisdom of crowd again, which you discussed last blog that using crowd source to accomplish a data journalistic project. So I would like to share a Chinese project with you, SinoGrids. It is a platform to encourage the public to upload their microcosmic data in order to shape a online city map. Here is the link( you can use Chrome to translate the web page to have a look):

    Good Day!


  2. I like the sentiment ‘don’t insult your audience’. It lines up nicely with what our colleague from Syria said in class yesterday: ‘Take into consideration the reader who knows, not the reader who doesn’t know. If the audience is big enough, the audience as a collective is bound to know. Strangely, outlets with big audiences sometimes still fail to take this into consideration.


    • I totally agree with Wernard’s post above. I really the part “don’t insult your audience”, I strongly agree with that, we always have to keep in mind various factors, regarding audience. Personally, I believe it is very interesting topic to analyse how audience perceives journalism, also, wide and full of different approaches. Anyway, great and clear post! I really enjoyed reading it!

      P.S. Now I’m also interested in your thesis – if it will be in English – would like to read it 🙂


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