Lancaster data scientist in Royal Statistical Society project to help researchers

Nicola Rennie
Dr Nicola Rennie

A data scientist from Lancaster Medical School has co-authored a guide for researchers to help them communicate the results of their research more effectively.

Nicola Rennie is one of three authors working on a project with the Royal Statistical Society (RSS) to develop guidance and best practices for visualising data and communicating statistics.

The guide Best Practices for Data Visualisation’ is written by Andreas Krause, Nicola Rennie, and Brian Tarran.

Nicola Rennie is a Lecturer in Health Data Science at Lancaster Medical School, and her teaching experience covers topics including data visualisation, programming in R and Python, and how to effectively communicate the results of statistical analyses.

She said: “As researchers, clearly communicating the findings of our research is vitally important - whether that's in an academic journal article, a conference presentation, or a social media post. Visualising those findings, and the data behind them, is a key part of this communication. Improving data visualisations can make it easier for readers to accurately identify patterns in data and understand key messages resulting from our research.

“Beyond image formats and resolution requirements, it's rare for journals to provide authors with guidance on charts and tables. We also can't expect authors, reviewers, or editors, who are unlikely to have received training in how to produce well-presented graphics, to be experts in data visualisation.

“That's why we put together the "Best Practices for Data Visualisation" guide. The overarching aim of the guide is to equip authors with the fundamentals for creating data visualisations that are high quality, effective at conveying information, and fulfil their intended purpose.”

The guide begins with an overview of why we visualise data, and then discusses the core principles and elements of data visualisations – including the structure of charts and tables, and how those structures can be refined to aid readability.

Concrete advice, examples, and code are presented to help improve the styling of charts, with a particular focus on accessibility. There’s a dedicated section on styling charts for RSS publications, and readers are also provided with links to resources for choosing the right type of chart for the data at hand.

“Although the guidance is published by the Royal Statistical Society, it's aimed at anyone who visualises data as part of their work. If you're a researcher who is creating a chart or a table, it will provide a step-by-step guide to help you create it in a clearer and more accurate way. We hope this guide can help all of us to do a better job of using data visualisation to communicate our research.”

The guide is free to read online, and source code and files are on GitHub.

The authors are hosting a session at the RSS International Conference in Harrogate this September where they plan to work with delegates to expand and add new content to the guide. For more details on the session, visit the RSS conference website.

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