Visual Thinking Lab

Declutter and Focus: Empirically Evaluating Design Guidelines for Effective Data Communication

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Collaborators: Kiran Ajani¹, Elsie Lee², Cindy Xiong³, Cole Nussbaumer Knaflic⁴, William Kemper³, Steven Franconeri^3
1Case Western Reserve University School of Medicine, ²University of Michigan School of Information, ³Northwestern University Department of Psychology, ⁴storytelling with data

Abstract Data visualization design has a powerful effect on which patterns we see as salient and how quickly we see them. The visualization practitioner community prescribes two popular guidelines for creating clear and efficient visualizations: declutter and focus. The declutter guidelines suggest removing non-critical gridlines, excessive labeling of data values, and color variability to improve aesthetics and to maximize the emphasis on the data relative to the design itself. The focus guidelines for explanatory communication recommend including a clear headline that describes the relevant data pattern, highlighting a subset of relevant data values with a unique color, and connecting those values to written annotations that contextualize them in a broader argument. We evaluated how these recommendations impact recall of the depicted information across cluttered, decluttered, and decluttered+focused designs of six graph topics. Participants were asked to redraw previously seen visualizations, to recall their topics and main conclusions, and to rate the varied designs on aesthetics, clarity, professionalism, and trustworthiness. Decluttering designs led to higher ratings on professionalism, and adding focus to the design led to higher ratings on aesthetics and clarity, and better memory for the highlighted pattern in the data, as reflected both by redrawings of the original visualization and typed free-response conclusions. The results largely empirically validate the intuitions of visualization designers and practitioners.