AI Article Synopsis
- Good data visuals help people understand patterns in things like science, health, and policy.
- Badly made visuals can confuse people and make them distrustful, especially if they don't know much about graphs.
- To make good visuals, designers should think about who will see them and follow certain guidelines that make them easy to understand.
Article Abstract
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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| http://dx.doi.org/10.1177/15291006211051956 | DOI Listing |
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