Knowledge Transfer Partnership.

Studying how humans interact with data visualisation.

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The world is bursting with data. Graphs, maps and statistics are everywhere. While there’s a huge spotlight on big data — and churning out as much data as possible — there’s only a handful of people investigating if anyone can understand it or use it to make decisions. To continue creating innovative and impactful visualisations, we’ve developed a research project together with the University of Cambridge to expand our knowledge of the psychology behind data visualisations.

We are investigating how the design of data visualisations can affect the way people respond to them, and we apply this new-found knowledge to improve our projects. The research is funded by Innovate UK, the UK’s innovation agency and is led by our Human-Computer Interaction Researcher, Melanie Herrmann, with support from two fantastic academics at the University of Cambridge: Will Skylark and Greg Davis.

This project assembles, for the first time, the academic, research and practical skills needed to test how humans interact with, understand and use digital information to make decisions for planetary benefit. Backed by this new knowledge, we are in a unique position to make visualisations that inform and empower millions of people to improve our planet.

Humans are complicated.

The human mind is complicated. Our judgements, opinions and choices can be counterintuitive, inconsistent and downright irrational—but that doesn’t stop us from making them. Through our research into the psychology of data interpretation and decision-making we develop practical guidelines that the whole data visualisation community can use to create designs with positive impacts.

A mix of methods.

We are using a range of methods to investigate how people understand data visualisation. Building on an initial review of best practices and theories, we have conducted studies with different users, collecting both qualitative and quantitative data about their visual information processing and learning experience. We are now scaling up our research to better evaluate our products, and build a science of data visualisation to direct out future work.