Photo by NASA on Unsplash

The psychology behind effective data visualisation.

Because data have feelings too!

In the coming weeks, we’ll be starting a two year research programme together with our partners in the Department of Psychology at the University of Cambridge. Our aim is to investigate how people interpret and understand our visualisations. We want to see if there are certain design principles we can use to make sure a given dataset talks to, is understood by, and can be useful to an individual making decisions that have an impact on the environment. And what’s more, we’re looking for someone to join us as a researcher on this project!

We’re really excited to be working with two excellent academic supervisors on this project. Will Skylark and Greg Davis are already doing fascinating work on the psychology of data interpretation and decision-making. Our aim is for the research we’ll do together to be a useful contribution to the literature around this topic, as well as a practical framework to help the whole community of data visualisers generate more impact with their data presentations.

But why is this research so interesting and important to us?

Well, there’s plenty of research out there on how to create effective visualisations, but we don’t fully understand the emotions people feel when they approach and respond to data; how do we go from someone reading an insight, to understanding it, to taking action? This is what we’d like to understand better, so we can create data visualisations that deliver a positive impact to the world. If you’re interested in working with us on this, check out the job listing here and read on for our introduction to the research we want to do.

Back to basics: Visualisations organise and simplify our world.

Imagine a graph. I bet it’s a bar chart, with the biggest bar on the left and trailing down to the smallest bar on the right. It’s a simple illustration of some variable (maybe population) and how it varies across different states of another variable (maybe countries). Or perhaps how deforestation rates have changed over time and over space, as in this example below.

Screenshot from Global Forest Watch Climate

Data visualisations organise and simplify things you often can’t see. How else can you truly get a sense of how much bigger China and India’s populations are without this kind of graph. Numbers are great, but having a visual means of comparison makes these observations much more apparent.

Making visualisations easier to interpret and understand.

Over the last decades, since Tufte’s seminal piece on data visualisation theory, we’ve seen the field of data visualisation evolve. A great deal of this has been afforded by advances in personal computing, the software we can use to create visualisations, and the opportunities of dynamic and interactive visualisations on the web.

And as new visualisation techniques have been created and old ones refined for a digital era, people have been trying to test the effectiveness of these different styles. The art of data visualisation is to communicate something clearly and effectively, so this research has been extremely useful to find the techniques that help readers understand the topic at hand.

Take this example, where researchers from the University of East Anglia investigated ways to make the visualisations published by the IPCC easier to understand. You can access the paper here. In particular they looked at a line graph depicting Northern Hemisphere snow cover during the 20th Century. Take a look at the graph below and tell me what the long-term trend is.

Originally from Summary for Policymakers, IPCC 2013

You’d think a simple line graph would be easy to interpret right? In this particular example you have a lot of localised variation, which can make it difficult to see the long-term variation. Perhaps you broke up the line into a series of smaller chunks in order to try and make sense of it? How much attention did you pay to the uncertainty (the shading around the line)?

On the basis of their experiments, the researchers demonstrated that adding some guidance and support helps users interpret the graph more accurately. We’ve also had a go at this ourselves with the new country pages on Global Forest Watch, as you can see in the graph below. Especially in cases like this, where the loss of millions of square kilometers is leading to significant changes to our environment, making data easier to interpret accurately is a necessary step towards global action to address climate change.

Check out how whether the rate of trees being cut down is normal or not on the new country pages on Global Forest Watch

What’s next? From effective to emotive visualisations.

But it’s just one step. As we all know, humans are complicated beings: in any one day we can go from messy and lazy to overly-caffeinated and hyperactive to emotional, flawed and vulnerable. Or perhaps you’re all of these at the same time!

All those emotions are at play when you read data. Well in fact, any time you learn anything. For the BBC aficionados around, think back to the latest series Blue Planet and Planet Earth over the last few years. You remember the teamwork between that fish and the octopus right? And the boiling ocean caused by Orcas? And the baby lizard running from the snakes? The emotions Attenborough and his team make you experience — awe, excitement, empathy — work together to make your brain more susceptible to learning and remembering things.

When it comes to data visualisation however, that research is a bit lacking. Helen Kennedy and Lucy Hill wrote about the “feeling of numbers” last year, and pulled together some of the leading examples of researchers trying to understand how the emotions you feel affect the way you approach and respond to data. They argue that “it is not only numbers but also the feeling of numbers that is important” when creating data visualisations and state that “the relationship between data and emotions has rarely been noted”.

Filling the gap.

And this is where our project with the Department of Psychology at the University of Cambridge comes in. Over the next two years someone will have the opportunity to work with us and two fantastic supervisors, Will and Greg, to investigate the emotional impact of data visualisation. We hope to understand how the design of different visualisations can affect the way people respond to them. This research could be applied to data that people use to plan a nation’s energy policy, or choose a chocolate bar that doesn’t destroy the rainforest.

Above all, we want the research to help people. We have an unequivocal commitment to our users; every day we’re working to make data usable, understandable, and useful to people all around the world. Maybe you’re reading this right now because you’ve used one of our websites before and learned something new (and if you haven’t, head over to right now!). With this research we’re looking to find the techniques that can deliver you even more informative, entertaining, affecting experiences. And who knows, maybe that’ll influence someone to take that decisive action that stops the sixth mass extinction, or gives clean energy to millions of impoverished people. We really believe the potential for good is limitless.