Discussion questions#
There is a tension between communicating the most information and knowledge effectively (Cairo) and working with the constraints of human visual perception (Franconeri et al.). Where does this tension come to a conflict when making data visualizations? Provide explicit examples.
Franconeri and colleagues show how framing (e.g., choice of highlighting, annotations, scaling) in data visualization can lead to fundamentally different conclusions from the same graphic. How should you implement a balance between making plotting choices to communicate results effectively and not biasing viewers to incorrect interpetations?