Guidelines
Suggest edit

Remove purely decorative visual elements

For explanatory charts aimed at mixed audiences, avoid decorative icons, colors, and stylistic embellishments on an already chosen chart to improve readability and mitigate distracting or confusing overdesign for viewers with varied confidence.

  • purpose:refine
  • basis:rhetorical
  • quality:readability
  • lever:encoding
  • polish:declutter
  • aesthetic:style:avoid

advice

Keep only relevant visual elements

Keep icons, colors, and stylistic treatments only when they serve the data message. For example, remove extra flags or directional markers that do not help interpretation, keep an icon only when it clearly stands for the measured concept, and use an intentionally low-threshold drawing style only when it helps less confident readers feel addressed.

reason

Why relevant styling works

Extra styling competes with the data when readers cannot tell whether it encodes information or merely decorates the display. Purposeful styling can still help when it signals the topic, makes the chart feel more approachable, or strengthens emotional connection to the message.

Mechanism: Relevant visual elements give readers a reason to attend to them. Decorative ones create extra things to parse, which some viewers experience as clutter or irritation rather than clarification.

Evidence: A public survey found mixed reactions to icons, markers, flags, and colors in an embellished comparison chart: some viewers liked them, while others found them irritating or “too much,” supporting removal of purely decorative additions (Saske et al., 2025). Practitioner accounts also describe using approachable hand-drawn visuals for less confident readers and crafting aesthetics to create attention and emotional connection when style is deliberately tied to the message (Schuster et al., 2023; Gregory et al., 2024).

Notes: This is a relevance test, not a ban on aesthetics.

context

Use when the chart has added visual styling

  • User Goal: Explain data clearly without losing audience attention.
  • Chart Setting: An already chosen chart includes added icons, symbolic markers, flags, extra colors, or illustrative styling beyond the core data marks.
  • Audience: Mixed viewers, including less confident readers.
  • Success Criterion: Viewers can see why each added visual element is there and do not read the chart as cluttered or “too much.”

exceptions

Do not apply it as a ban on all aesthetics

Break it when: the added visual element directly signals the topic, makes the chart more approachable for less confident readers, or is intentionally crafted to deepen emotional connection to the message. Why: in those cases the styling is doing communicative work rather than acting as decoration.

costs

Costs of removing decorative styling

Sacrifice: Some immediate visual flair or attention-grabbing appeal. Risk: If applied too rigidly, the chart can feel less inviting or less emotionally resonant. Mitigation: Keep only the style moves you can point to as supporting the topic, audience approachability, or message.

mistakes

Common failures with chart styling

  • Mistake: Keeping several icons, colors, and symbolic markers after they stop adding meaning. Why it fails: readers can experience the chart as irritating or overloaded.
  • Mistake: Stripping all style from the chart, even when style is the device that makes the message approachable or resonant. Why it fails: the chart may lose audience connection.

check

Check whether the styling is doing real work

Failure Sign: Reviewers describe the styling as “too much” or cannot explain what an extra icon, marker, or color is doing. Quick Check: Point to each non-data visual element and state its specific message role; if its role is only decoration, remove it. Stronger Test: Show a version with and without the added styling to a few target viewers and note whether the styled version clarifies the message or only adds visual interest.

fix

Fix decorative overdesign

  • Delete icons, flags, markers, or extra colors that do not change what the reader can infer.
  • Keep one icon or style cue only when it clearly names the topic or measured concept.
  • Replace a pile of embellishments with one deliberate style treatment if you need a more approachable tone.
  • Rework color and form so they strengthen the message instead of sitting beside it as decoration.

References

Gregory, K., Koesten, L., Schuster, R., Möller, T., & Davies, S. (2024). Data Journeys in Popular Science: Producing Climate Change and COVID-19 Data Visualizations at Scientific American. Harvard Data Science Review, 6(2). https://doi.org/10.1162/99608f92.141c99cf
Saske, A., Koesten, L., Möller, T., Staudner, J., & Kritzinger, S. (2025). A Multidimensional Assessment Method for Situated Visualization Understanding (MdamV). arXiv. https://doi.org/10.48550/arXiv.2410.23807
Schuster, R., Koesten, L., Möller, T., & Gregory, K. (2023). Who is the Audience? Designing Casual Data Visualizations for the “General Public.” arXiv. https://doi.org/10.48550/arXiv.2310.01935