Publications by authors named "A Slingsby"

Article Synopsis
  • The report discusses a collaboration between epidemiological modellers and visualization researchers to improve the understanding and modeling of the COVID-19 pandemic through existing visualization techniques.
  • It highlights the effectiveness of visualization in epidemiological research, identifies ongoing challenges in the field, and offers recommendations for future collaborations.
  • The goal is to encourage both scientific and visualization communities to work together, leveraging their strengths to tackle significant data-related challenges in epidemiology and other areas.
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The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more.

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Fundamental to the effective use of visualization as an analytic and descriptive tool is the assurance that presenting data visually provides the capability of making inferences from what we see. This paper explores two related approaches to quantifying the confidence we may have in making visual inferences from mapped geospatial data. We adapt Wickham et al.

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Small multiples enable comparison by providing different views of a single data set in a dense and aligned manner. A common frame defines each view, which varies based upon values of a conditioning variable. An increasingly popular use of this technique is to project two-dimensional locations into a gridded space (e.

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