A review of uncertainty visualization errors Working memory as an explanatory theory 1st edition by Lace Padilla, Spencer Castro, Helia Hosseinpour

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Author: Lace Padilla, Spencer C. Castro, Helia Hosseinpour

Uncertainty communicators often use visualizations to express the unknowns in data, statistical analyses, and forecasts. Well-designed visualizations can clearly and effectively convey uncertainty, which is vital for ensuring transparency, accuracy, and scientific credibility. However, poorly designed uncertainty visualizations can lead to misunderstandings of the underlying data and result in poor decision-making. In this chapter, we present a discussion of errors in uncertainty visualization research and current approaches to evaluation. Researchers consistently find that uncertainty visualizations requiring mental operations, rather than judgments guided by the visual system, lead to more errors. To summarize this work, we propose that increased working memory demand may account for many observed uncertainty visualization errors. In particular, the most common uncertainty visualization in scientific communication (e.g., variants of confidence intervals) produces systematic errors that may be attributable to the application of working memory or lack thereof. To create a more effective uncertainty visualization, we recommend that data communicators seek a sweet spot in the working memory required by various tasks and visualization users. Further, we also recommend that more work be done to evaluate the working memory demand of uncertainty visualizations and visualizations more broadly.

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Tags: A review, uncertainty visualization, Working memory, explanatory theory, Lace Padilla Spencer Castro, Helia Hosseinpour