Robert G. Picard explains how new visualisation techniques can aid our understanding of complex data.
Large-scale and complex data create challenges for businesses, government, and civil society organisations to act upon and is now leading scholars and other researchers to seek new data visualisation techniques that improve the presentation and understanding of their results.
The needs to improve visualisation and the best methods for doing so are outlined in a new report, ‘Making Research Useful: Current Challenges and Good Practices in Data Visualisation’, published in a joint project between the Reuters Institute for the Study of Journalism and the Department of Politics and International Relations at the University of Oxford, and the Alliance for Useful Evidence (a partnership between Nesta, the Big Lottery Fund, and the Economic and Social Research Council).
Data visualisation should tell a story
The report argues that data visualisation is more than a mere presentation of results with the use of graphics and pictures but involves the combination of data to illustrate patterns, connections, and schemes in ways that make the underlying data more understandable. It advises that data visualisation should tell a story, not merely present data, and that researchers can build the narrative from the data in ways that better involve its users.
The primary purpose of visualisation is to make application of the data more apparent, to overcome numeric anxiety and statistical ignorance in much of the public, to increase understanding among those who can apply the knowledge, and to help research results have greater impact on society.
A growing expectation
The visual display of information has been becoming the norm for several decades, partly because people tend to remember visual information more than textual information, partly because of the impact of high television viewing, partly because print media have increasingly used infographics, and partly because online media are increasingly providing multimedia presentations, mapping, interactive graphics, interactive video, and data calculators. These factors have created a growing public expectation of the visual display of information.
The research found that the biggest impediment to effective visualisation is that most researchers aren’t adept at creating visuals and that the charting options in standard word processing and statistical software are elementary, static, and only allow researchers to convey limited understanding. Better visualisations try to link images to the topic and include comparative concepts that improve rapid understanding. They tend to uses the concepts that most people understand; such as difference, size, position, sequence, series, time, and cause and effect.
Good data visualisation is most likely to occur when dissemination planning is incorporated early in research and adequate time to consider and prepare effective visualisations is provided at the end of the research project. Researchers require access to data visualisation tools and at times may need to work with designers and data specialists to improve visualisation.
Learning how to create better visualisation and what tools are available to improve them needs to become a priority for researchers, according to the report, which provides lists of resources and outlines the best practices that current exist in data visualisation.
Views expressed are the author’s own and do not necessarily represent those of the Alliance for Useful Evidence. Join us (it’s free and open to all) and find out more about the how we champion the use of evidence in social policy and practice.