EDS 240: Discussion 7

Peer feedback

Week 7 | February 18th, 2025

Consider high-level feedback . . .

where the focus is on whether a data visualization is accurate, relevant and understandable for the intended audience


  • does the visualization address the defined question? if so, how? if not, what’s missing or confusing?
  • what important trends do you see? are your eyes drawn to them? if yes, how? if no, how can you better highlight them?
  • what other context might be helpful for understanding this visualization (maybe the author has already considered this for the final deliverable!)?
  • is this visualization approachable for its intended audience? if yes, how so? if no, why not?
  • consider the graphic form – does it make sense for these data types?

. . . and detail-oriented feedback:

where the focus is on aesthetics choices (e.g. colors, typefaces, layout, themes, white space, etc.) and how those choices help to enhance / tell the story


  • is the color palette colorblind-friendly?
  • are colors used to convey any messages or overall theme? would you change them to improve this?
  • are the typefaces legible? do they contribute to the overall theme?
  • do elements look crunched or appropriately spaced out?
  • any non-data elements that should be moved or removed for clarity or simplicity?

Remember: all critiques should be accompanied by actionable recommendations for improvement!

With a partner:

  1. Take 10 minutes to review your partner’s viz and jot down (in the notes section of their Google slide):
  • 1 thing you really love / find effective
  • 1 piece of high-level feedback + suggest an alternative approach
  • 1 piece of detailed-oriented feedback + suggest an alternative approach
  1. Spend 10 minutes exchanging feedback and discussing your visualizations


20:00

In the last ~25 minutes of section, we’ll do a rapid fire share out of feedback. Please be prepared to share with the class:

  • 1 thing your partner really enjoyed and why
  • 1 thing your partner saw as an area for improvement + a suggested alternative

Data viz thought exercise of the week

Consider how adding context can make your visualization more compelling / tell a more complete story

Watch this on your own time!