On #datavis judging: John Schwartz’s advice

4 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?
Data visualisation is much more about narrative and explanation than about graphical flourishes. It is about arranging information so your audience can clearly see the patterns and trends. In a good visualisation the data stops being just numbers and starts telling stories, explaining facts and advancing arguments.

What are your data visualisation pet peeves?
At Soapbox we sometimes get asked to do ‘data visualisations’ for ideas that are really more matters of opinion or conjecture. In other words, the client wants to use the visual paraphenalia and positive associations of infographics to make something look more fact-based than it really is.

Design is visual language, so if you make something look like a data visualisation you are implicitly saying that your argument is backed up by evidence. If it is not backed by evidence, then you are more or less being dishonest. It’s depressing how often researchers in think tanks can’t grasp this point.

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?
I spend a lot of time looking at spreadsheet data using the conventional graphing tools that come with Excel. I would start by just selecting a bunch of data and clicking on different graphs to see what patterns emerge. Once you have an idea what your graphs are showing you, write it down in a couple of paragraphs or bullet points. Then write a headline for your paragraphs as if it was newspaper story. Those things will give you a foundation to start looking at the data in an original way and tie it into the story you want to tell.

Do you have a favourite data visualisation from outside the competition? What is it and why?
The periodic table of the elements is the greatest ever data visualisation. By arranging the elements by atomic weight Dmitri Mendeleev was able to identify recurring trends in physical properties and even predict the properties of some then undiscovered elements. The periodic table opened up chemistry to much wider audience – which is why you can see it in poster form in pretty much every science classroom in the world.