5 Tips for Creating Effective Data Visualizations

Data visualization transforms complex data into information that people can more easily understand and use. Data visualization is especially useful for education agencies, who often need to communicate different levels of data to audiences with different levels of data knowledge and different information needs.

Poorly designed data visualizations can lead users to misread trends, misunderstand differences, or draw inaccurate conclusions. Thoughtful data visualization can help bridge the gap between data collection and data-informed action.

Here are five tips for creating data visualizations that are clear, accurate, accessible and actionable.

1. Lead with what matters.

Place the most important information at the forefront of your visualization. A well-designed visualization should help the audience quickly identify key information and draw meaningful conclusions. Before creating a visualization, consider your audience and its purpose. What does your audience need to know? What should they be able to understand or do after viewing the visualization? Use the answers to these questions to determine which information to emphasize.

In the How Do Searchers Use ERIC? infographic, the most important information is placed clearly at the top.

2. Prioritize simplicity and clarity.

Showing more information is not necessarily better. Too much information, decoration, or unnecessary formatting can distract or overwhelm viewers and make it harder to identify the main takeaway. Keep visualizations clear by removing elements that do not communicate meaningful information. Use labels, colors, lines, and other visual elements intentionally, and give the data enough space to be skimmed and understood easily.

Example of a cluttered data visualization compared with a clearer version. Source: Forum Data Visualization Course

3. Be consistent and accurate.

Present information consistently so audiences can more easily understand and compare data. For example, if you publish a monthly report, maintain a consistent format from month to month so readers know where to find key information. Charts and graphs should also represent data accurately. Use consistent intervals on axes, clearly label units and categories, and avoid design choices that could exaggerate or minimize differences in the data.

Examples of annual year-in-review infographics for 2018 and 2019 that similarly format data visualization. Source: What Works Clearinghouse

4. Provide sources and context.

Identify the sources used in your visualization so readers understand where the information comes from and can better assess its reliability. Whenever appropriate, provide additional context such as the date or time period represented, population included, definitions of key measures, or other information necessary to interpret the data. Providing this context helps audiences draw more informed conclusions and increases transparency and trust in the information being presented.

Example of an effective data visualization that clearly identifies the data source. Source: How Do Searchers Use ERIC?

5. Design for accessibility.

Accessibility should be considered throughout the design process rather than added after a visualization is complete. Considering accessibility means

  • ensuring compatibility for screen readers and other assistive technologies;
  • minimizing jargon, acronyms, and technical terms;
  • using clear, easy-to-read fonts and text sizes;
  • using color intentionally and avoiding color as the only way to communicate meaning; and
  • providing text descriptions accurately convey the meaning of the visual content.

Examples of accessible data visualizations that pass a color contrast checker. Source: Forum Guide to Data Visualization

Turning Data into Action

Effective data visualization is about more than making data visually appealing. It is about helping people understand information, identify meaningful patterns, and make informed decisions. By prioritizing clarity, accuracy, context, consistency, and accessibility, education agencies can create visualizations that help turn data into meaningful action. For more information on data visualization, check out these QIP-supported resources:

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