Data visualisations are useful for providing insight from complex scientific data. However, even with visualisation, scientific research is difficult for non-scientists to comprehend. When developed by designers in collaboration with scientists, data visualisation can be used to articulate scientific data in a way that non-experts can understand. Creating human-centred visualisations is a unique challenge, and there are no frameworks to support their design. In response, this thesis presents a practice-led study investigating design methods that can be used to develop Non-Expert User Visualisations (NEUVis), data visualisations for a general public, and the response that people have to different kinds of NEUVis. For this research, two groups of ten users participated in quantitative studies, informed by Yvonna Lincoln and Egon Guba’s method of Naturalistic Inquiry, which asked non-scientists to express their cognitive and emotional response to NEUVis using different media. The three different types of visualisations were infographics, 3D animations and an interactive installation. The installation used in the study, entitled 18S rDNA, was developed and evaluated as part of this research using John Zimmerman’s Research Through Design methodology. 18S rDNA embodies the knowledge and design methods that were developed for this research, and provided an opportunity for explication of the entire NEUVis design process. The research findings indicate that developing visualisations for the non-expert audience requires a new process, different to the way scientists visualise data. The result of this research describes how creative practitioners collaborate with primary researchers and presents a new human-centred design thinking model for NEUVis. This model includes two design tools. The first tool helps designers merge user needs with data they wish to visualise. The second tool helps designers take that merged information and begin an iterative, user-centred design process
