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The visual system evolved and develops to process the scenes, faces, and objects of the natural world, but people adapt this powerful system to process data within an artificial world of visualizations. To extract patterns in data from these artificial displays, viewers appear to use at least three perceptual tools, including a tool that extracts global statistics, one that extracts shapes within the data, and one that produces sentence-like comparisons. A better understanding of the power, limits, and deployment of these tools would lead to better guidelines for designing effective data displays.
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The Science of Visual Data Communication: What Works
Effectively designed data visualizations allow viewers to use their powerful visual systems to understand patterns in data across science, education, health, and public policy. But ineffectively designed visualizations can cause confusion, misunderstanding, or even distrust—especially among viewers with low graphical literacy. We review research-backed guidelines for creating effective and intuitive visualizations oriented toward communicating data to students, coworkers, and the general public. We describe how the visual system can quickly extract broad statistics from a display, whereas poorly designed displays can lead to misperceptions and illusions. Extracting global statistics is fast, but comparing between subsets of values is slow. Effective graphics avoid taxing working memory, guide attention, and respect familiar conventions. Data visualizations can play a critical role in teaching and communication, provided that designers tailor those visualizations to their audience.
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- Award ID(s):
- 1901485
- PAR ID:
- 10367215
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- Psychological Science in the Public Interest
- Volume:
- 22
- Issue:
- 3
- ISSN:
- 1529-1006
- Page Range / eLocation ID:
- p. 110-161
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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