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Article published In:
Information Visualization
Edited by Isabel Meirelles, Marian Dörk and Yanni Loukissas
[Information Design Journal 27:1] 2022
► pp. 115–125

Visualising vapours

Graphical representation of Covid-19 transmission

ORCID logo | The BMJ (British Medical Journal)London, UK
The case study describes the process of designing an interactive visualisation tool to help people understand the likelihood of Covid-19 transmission in different situations. This visualisation was created as part of a 13 month long collaborative project between scientific experts from a UK government advisory group, and a multimedia team at The BMJ (British Medical Journal). The data underpinning the graphic was collected from 27 experts via a knowledge elicitation study. It includes discussion of lessons learned about collecting and visualising uncertain data, and the benefits of user testing.
Keywords: Covid-19, infectious disease, visualisation, user testing, interactivity, knowledge elicitation
Article outline
  • The problem
  • The seed of an idea
  • Developing the visualisation
  • Testing and refinement
  • Publication
  • Reflection and learning
  • References
Available under the Creative Commons Attribution-NonCommercial (CC BY-NC) 4.0 license.

For any use beyond this license, please contact the publisher at [email protected].

Published online: 21 November 2022
DOI logo
https://doi.org/10.1075/idj.22007.sta
References (9)
References
Cairo, A. (2016). The Truthful Art: Data, charts, and Maps for Communication. New Riders.Google Scholar
Cleveland, W. & McGill, R. (1985). Graphical Perception and Graphical Methods for Analyzing Scientific Data. Science, 2291, 828–833. DOI logoGoogle Scholar
Freeman, A. L. J., Parker, S., Noakes, C., Fitzgerald, S., Smyth, A., Macbeth, R., Spiegelhalter, D. & Rutter, H. (2021). Expert elicitation on the relative importance of possible SARS-CoV-2 transmission routes and the effectiveness of mitigations. BMJ Open, 11(12). DOI logoGoogle Scholar
Hengesbach, N. (2022). Undoing Seamlessness: Exploring Seams for Critical Visualization [preprint]. [URL]
Kirk, A. (2019). Data Visualisation: A Handbook for Data Driven Design (2nd Ed). SAGE.Google Scholar
Nielsen, J. (2012). How many test users in a usability study? [URL]
Rutter, H., Parker, S., Stahl-Timmins, W., Noakes, C., Smyth, A., Macbeth, R., Fitzgerald, S. & Freeman, A. (2021). Visualising SARS-CoV-2 transmission routes and mitigations. The BMJ. 3751. DOI logoGoogle Scholar
Sless, D. (2008). Measuring information design. Information Design Journal 16(3), 250–8. DOI logoGoogle Scholar
Spiegelhalter, D., Pearson, M. & Short, I. (2011). Visualizing uncertainty about the future. 3331, 1393–400. DOI logoGoogle Scholar