Things to Consider
Do you need a data visualization?
- If the significance of the data can be concisely expressed with statistics, then you may not need a data visualization.
What's the right data visualization for your work?
- Who is the audience?
- Focus on reducing the cognitive load.
- Avoid too much data.
- Avoid 3D visualizations.
- Utilize a tool that helps with identifying suitable data visualizations for your needs, such as Data Viz Project.
Ethically represent the data.
- Don't distort the range of data represented.
- Don't cherry pick what is represented by the data visualization.
- Clearly label the data.
Think about colors.
- According to the National Eye Institute, 1 in 12 men and 1 in 200 women have color vision deficiencies. Using colors alone to express data prevents some from understanding the data being visualized.
- Utilize colorblind friendly color combinations
- "Use different shapes, patterns, textures, or labels" (Ferreira)
- "High-contract color pairings cause viewers to perceive greater degrees of data disparity." (Bowers)
Tell a Story
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Reference
Numbers Shouldn't Lie: An Overview of Common Data Visualization Mistakes (Micah Bowers)
Two Simple Steps to Create Colorblind-Friendly Data Visualizations (CR Ferreira)