The Datatext: A Multilevel-discursive Theory For Improved Public Health Data Visualizations

Abstract

In the run up to the COVID-19 lockdown in March 2020, Prime Minister Boris Johnson challenged the British public to “squash the sombrero,” and so save thousands of lives in the event of the pandemic overburdening an already stretched National Health Service. There was a jarring sense of incongruity between this tabloid metaphor, and the minimalist line-graph to which the prime minister was referring. Best practice in infographic design may be well-suited to the communication of data amongst scientists and other literate audiences. But today matters of public health are subject to debate between citizens who are actively engaged in creating and circulating knowledge amongst wider publics with variable levels of literacy. Here a different epistemic approach, and different assumptions about design, are required. When conceiving of the infographic in public health as a multilevel discourse containing visual arguments mutually re-enforced by combinations of words, numbers and images, what I call a datatext (after W.J.T. Mitchell), it may be possible to design more effective communications. In this paper I set out a theoretical approach to infographic design drawing upon image schema theory, as well as conventional best practice. I conclude with recommendations for designing effective datatexts for optimal biocommunicability.