On #datavis judging: Enrique Mendizabal’s advice

19 November 2013
SERIES Think tanks & data visualisation 12 items

Round 3 of the On Think Tanks Data Visualisation Competition is currently open for submissions. We’ve had some great entries in both Round 1 and Round 2, but this is the last open call for entries (the deadline is 20 November at 23:59 GMT!)!

The judges want it to be the biggest and the best round we’ve had so far so each of them has taken a minute to offer their advice when it comes to data visualisation — what works, what doesn’t, and what are they really looking for when judging the data visualisations. We’ll be posting their thoughts over the next couple of weeks.


In your opinion, what makes a good data visualisation?
I think a good visualisation is one that presents an argument – or better yet, allows its audience to arrive at the argument the visualisation is trying to make. A good visualisation is also visually engaging. It need not be ‘beautiful’ but should convey, in its design, a mood or feeling: should we be outraged by the ‘inequality’, curious about the ‘new trends’, shocked at the ‘unexpected levels of corruption’?

What are your data visualisation pet peeves?
When the focus is the design and not the story. Sometimes their designs have been driven by an effort to make them look original and innovative and the information and arguments they are supposed to make have been clearly relegated in importance. A simple design can be far more powerful.

Another pet peeve is related to their use. Sometimes they appear to be stand alone efforts. The best visualisations always encourages you to search for more information on a subject. They have to be connected to a wider communication effort.

What one piece of advice would you give to someone staring down a spreadsheet full of data and who is interested in making it more accessible?
Have a look at what others have done before. Don’t be afraid of using designs that work, and tools that already exist, and that people already know how to ‘read’.

Do you have a favourite data visualisation from outside the competition (can you narrow it down to one)? What is it and why?
In the 1990s the Peruvian government started using a map of Peru that showed the country’s mountain ranges and valleys in detail – in relief. The map is now widely used and it changed the way we thing of the country: from political divisions to the more appropriate geographic similarities and differences that often divide communities a few hundred meters from each other. It’s a great example because, although a map is one of the most basic and longest-existing forms of data visualisation, this one really changed how people understood something.