0. Definitions

What is data visualization?

A few definitions of data visualization:

The rendering of information in a visual format to help communicate data while also generating new patterns and knowledge through the act of visualization itself (Du Bois et al., 2018, p. 8)

Du Bois, W. E. B., Battle-Baptiste, W., & Rusert, B. (2018). W.E.B Du Bois’s data portraits: Visualizing Black America (First edition). The W.E.B. Du Bois Center At the University of Massachusetts Amherst ; Princeton Architectural Press.

The representation and presentation of data to facilitate understanding (Kirk, 2016, p. 19)

Kirk, A. (2016). Data visualisation: A handbook for data driven design. SAGE.

It’s pretty common to find a book with hundreds of pages of details on data visualization, but no definition.

What else could we add here?

What should visualization do?

Data visualization is part art and part science. The challenge is to get the art right without getting the science wrong and vice versa. A data visualization first and foremost has to accurately convey the data. It must not mislead or distort…. At the same time, a data visualization should be aesthetically pleasing (Wilke, 2019, ch 1)

Wilke, C. (2019). Fundamentals of data visualization: A primer on making informative and compelling figures (First edition). O’Reilly. https://clauswilke.com/dataviz/

Why visualize data?

• Explore
• Explain
• Both

What’s the difference, and what happens in the overlaps?

How is data visualization used?

Brainstorming

Positive / constructive

• facilitates & documents change
• highlights social justice concerns
• justifying decisions
• telling a story
• connecting dots
• inform
• efficiency & safety
• elicit emotion
• convey lots of information
• make data more understandable

Negative / destructive

• facilitates & documents change in ways that are harmful
• telling a story (misinformation)
• elicit emotion (sensationalize)