This post was originally featured on AEA365, the daily blog of the American Evaluation Association during the Data Visualization and Reporting week.
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Years ago, when I first learned about data visualization, I went all in. I read books and blogs, listened to podcasts, attended workshops, and poured over the guiding principles. I thought that if I understood the rules, then I could get it “right.”
But focusing on getting things “right” presents challenges. It perpetuates dichotomous thinking and stifles creativity. It often prioritizes Western ways of thinking and leaves out community voice. It raises criticism rather than encouraging conversation.
When we focus solely on the dos and don’ts of data visualization, feedback begins to sound like: always start your axis at zero, do not reverse your axis, never use a pie chart, or stay away from the color red. (None of those statements are true 100% of the time.) Spoiler alert, hiding these comments in an oreo cookie feedback format often still sounds critical.
Lessons Learned:
Switching our thinking from getting it “right” by following the rules to getting it “right” by serving the greater purpose, client, and community changes the feedback. By shifting the focus, we welcome in conversation, creativity, and curiosity.
Questions to ask when giving feedback about a visualization include:
- What type of feedback are you looking for on this visualization?
- What was your process for creating this visualization?
- What are the key takeaways you would like readers to know?
Questions to ask when seeking feedback about a visualization include:
- What did you notice about this visualization?
- What questions came up for you after seeing this visualization?
- How might you use this visualization to inform decisions?
Key phrases to think about when giving feedback:
- I wonder…
- I suggest…
- Tell me more about…
- I’m curious about…
- You may consider…
- What do you think about…
These questions and phrases help us to understand what choices went into the design, the potential impact of the visual, and where feedback may or may not be desired.
Rad Resources:
- Storytelling with data: #1 the art of feedback – this podcast with Cole Nussbaumer Knaflic describes giving and receiving data visualization feedback, including specific examples from the Storytelling With Data makeover challenge.
- Data Visualization Feedback: Evaluating Choices, Not Checklists – this Nightingale article by Joshua Smith encourages readers to focus on design choices rather than principles when reviewing visualizations.
- On Giving and Receiving Critique in DataViz Communities – this blog by Ben Jones talks about giving and receiving feedback on data visualizations, especially when it is unsolicited.
- Soft Landing, Firm Impact: Practical Tips on How to Give and Receive Meaningful Data Visualization Feedback – this Outlier Conference presentation by Candra McRae provides suggestions for being clear and humble when giving and receiving feedback.