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Michigan State University

Data Visualization Guide: Best Practices

Resources to support MSU students, faculty, staff, and community members in effectively communicating through data visualizations.

General Best Practices

There are numerous strategies to creating effective data visualizations, with varying levels of detail. Before diving into one of these strategies and creating visualizations, consider the following questions:

  • Who is my intended audience?
  • What message do I want them to take away from this visualization?

Having a clear audience and message in mind from the start will help as you begin to create your data visualizations.

Stephen Few's Data Visualization Effectiveness Profile

Stephen Few, a prominent figure within the Data Visualization community, lists seven criteria to judge the effectiveness of a visualization:

  1. Usefulness - Does the visualization meet the audience's needs?
  2. Completeness - Does the visualization contain all the information needed to understand the message and nothing more?
  3. Perceptibility - Does the visualization display the information clearly with minimal effort required from the audience?
  4. Truthfulness - Is the visualization accurate and valid?
  5. Intuitiveness - Is the visualization familiar and easy to understand?
  6. Aesthetics - Is the visualization pleasing to the eye of the audience?
  7. Engagement - Does the visualization invite the audience to view and examine the information?

Stephen Few. (2017). Data Visualization Effectiveness Profile. Visual Business Intelligence Newsletter.

Other Strategies for Best Practices