Enhancing Visual Encodings of Uncertainty Through Aesthetic Depictions in Line Graph Visualisations

The method of representing uncertainty can drastically influence a user’s interpretation of the visualised data. Whilst reasons for the scarce adoption of accepting uncertainty visualisations has been extensively researched, exploring further intuitive depiction methods has taken a back seat. Currently, most visualisation methods for uncertainty revolve around the comprehension of grasping pre-existing techniques such as confidence intervals and error bars. Moreover, this anticipates that the intended audience will be proficient in obtaining the relevant information displayed. To help establish an accessible method for the visualisation of uncertainty, we adopt a novel cross-disciplinary approach to further understand and depict the more intuitive/affective dimensions of uncertainty. The field of aesthetics is mostly associated with the discipline of art and design, but it has been applied in this research to evaluate its effectiveness for uncertainty visualisation. In a recent study with one thousand one hundred and forty-two participants, the authors examined the influence of applying aesthetic dimensions to the visualisation of a line graph. We find that certain aesthetic renderings afford a higher degree of uncertainty and provide an intuitive approach to mapping uncertainty to the data. By analysing the participants’ responses to different aesthetic renderings, we aim to build a picture of how we might encourage the use of uncertainty visualisation for a lay audience.