Data visualization
Learning goals
After completing this assignment, students should be able to:
- Discuss the role of emotion in data visualization in the context of best practices and data feminism
- Describe the tension in data visualization between the perceived objectiveness of data analysis and the necessary role of uncertainty
Content
- Read:
- D’Ignazio and Klein (2020), Ch. 3 - On Rational, Scientific, Objective Viewpoints from Mythical, Imaginary, Impossible Standpoints
- Supplementary reading (optional):
- Joint Statistical Meeting Data Art Show
- Silver, Why FiveThirtyEight Gave Trump A Better Chance Than Almost Anyone Else, Nov 11, 2016.
- Silver, The Real Story Of 2016, Jan 19, 2017.
- Cohn and Katz, The Needle’s Back. Maybe This Time, It Will Really Be Wrong, Mar 13, 2018.
In-class activity
Possible discussion topics:
Conventions for data visualization:
After doing a sociological analysis, Helen Kennedy and coauthors determined that four conventions of data visualization reinforce people’s perceptions of its factual basis: (1) two-dimensional viewpoints, (2) clean layouts, (3) geometric shapes and lines, and (4) the inclusion of data sources at the bottom. These conventions contribute to the perception of data visualization as objective, scientific, and neutral. (p. 82)
Emotion in data visualization:
It is important to note that emotion and visual minimalism are not incompatible here; the Periscopic visualization shows us how emotion can be leveraged alongside visual minimalism for maximal effect. (p. 84)
Uncertainty (HUGE idea):
As it turns out, visceralizing data may help designers solve one particularly pernicious problem in the visualization community: how to represent uncertainty in a medium that’s become rhetorically synonymous with the truth. (p. 88)
Assignment
Respond to the following prompts on a single piece of paper.
In one paragraph, discuss the role that emotion plays in data visualization, in the context of both best practices in data visualization and data feminism.
In one paragraph, reflect on your own feelings about objectivity in data analysis.
Submission
Hand in before leaving the classroom.
Rubric
| Criteria | Zero | One |
|---|---|---|
| Overall Quality | Incomplete or missing submission. Student did not make an earnest effort to complete the assignment. Formatting errors make the submission unreadable. | Student accurately summarizes the content of the reading. Student’s reflection is thoughtful and genuine. |