Graphical design: Elevating emotion in data viz

Lecture 15

Dr. Benjamin Soltoff

Cornell University
INFO 3312/5312 - Spring 2025

March 18, 2025

Announcements

Critique of traditional power structures in data science

Examining power – data is never neutral
Challenging power – question and challenge dominant hierarchies and biases embedded in data practices
Elevating emotion and embodiment – value emotion and lived experience as legitimate sources of knowledge
Rethinking binaries and hierarchies – seek more fluid and inclusive representations
Embracing pluralism – promote diverse perspectives to create more inclusive and ethical data practices.
Considering context – data must be interpreted within its social, historical, and political context to avoid misleading conclusions
Making change – data should be used to advance social justice and work toward more equitable outcomes

Data science and statistics as neutral or logical approaches
Historically dismisses emotion, intuition, and lived experiences as subjective
Critiquing the myth of objectivity in data science
Frame your work in your positionalities and lived experiences

Representations of data that the whole body can experience, emotionally as well as physically.

We are recapturing the human dignity of each one of these people who have been compressed and … reduced to numbers.

– Suzanne Brennan Firstenberg

Instructions

Go to the course GitHub org and find your ae-14 (repo name will be suffixed with your GitHub name).
Clone the repo in RStudio, run renv::restore() to install the required packages, open the Quarto document in the repo, and follow along and complete the exercises.
Render, commit, and push your edits by the AE deadline – end of the day