Many of us were taught to read and write text, but few know the basic rules of creating and interpreting powerful visuals. We will focus on elements of visual communication, including color, chart choice, and other attributes.
Visual literacy is the ability to understand, interpret, and evaluate visual messages. Visualization literacy is the ability to confidently use a given data visualization to translate data questions into visual queries (Boy, et al., 2014).
The resources listed below can provide some guidance when selecting a chart and communicating your data. It is critical to remember that design choices are not neutral. See the post on You Say Data, I Say System by Jer Thorp for some background. We will talk about this more in the next session.
- There are any number of collections of data viz options. For chart ideas, take a look at the Data Viz Project, The Chartmaker Directory, or The Data Visualization Catalogue.
- Qualitative Chart Chooser by Stephanie Evergreen
- Chart Suggestions: A Thought Starter by Andrew Abela
- The Graphic Continuum by Jon Schwabish
- The Data Visualization Checklist by Ann K. Emery and Stephanie Evergreen
It may also be helpful to read about what questions to ask when creating charts.
The same data set can look very different depending upon which chart you choose. Visit visualizing distributions for some examples, but there is additional background on how the same stats can lead to different graphs.
Color can be very tricky. This is a complex topic that we could spend an entire session on. There are some resources on Pinboard, including palettes, tools for evaluating for people with vision issues, and best practices from the research.
Bartram, L., Patra, A., & Stone, M. (2017, May). Affective Color in Visualization. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (pp. 1364-1374). ACM.
Bertini, E., Elmqvist, N., & Wischgoll, T. (2016). Judgment error in pie chart variations.
Brehmer, M., Lee, B., Bach, B., Riche, N. H., & Munzner, T. (2017). Timelines revisited: A design space and considerations for expressive storytelling. IEEE transactions on visualization and computer graphics, 23(9), 2151-2164.
Gannon-Slater, N., Gannon-Slater, N., La Londe, P. G., La Londe, P. G., Crenshaw, H. L., Crenshaw, H. L., ... & Schwandt, T. A. (2017). Advancing equity in accountability and organizational cultures of data use. Journal of Educational Administration, 55(4), 361-375.
Gleicher, M. (2017). Considerations for Visualizing Comparison. IEEE Transactions on Visualization and Computer Graphics.
Sarikaya, A., & Gleicher, M. (2017). Scatterplots: Tasks, data, and designs. IEEE Transactions on Visualization and Computer Graphics.
Skau, D., & Kosara, R. (2016, June). Arcs, angles, or areas: individual data encodings in pie and donut charts. In Computer Graphics Forum (Vol. 35, No. 3, pp. 121-130).
Walny, J., Huron, S., Perin, C., Wun, T., Pusch, R., & Carpendale, S. (2017). Active Reading of Visualizations. IEEE Transactions on Visualization and Computer Graphics.
Check out Dear Data, "a year-long, analog data drawing project by Giorgia Lupi and Stefanie Posavec, two award-winning information designers living on different sides of the Atlantic. By collecting and hand drawing their personal data and sending it to each other in the form of postcards, they became friends."
Visit the Instagram feed of data editor Mona Chalabi for hand drawn charts on a variety of topics. Also, check out the work of Catherine Madden who integrates data, design, and drawing.
Elijah Meeks has shared some background on the gestalt principles for data visualization. Also check out this article on five ways you can use gestalt principles for powerful imagery.
Visualization strategies are for more than just quantitative data. Take a look at ways to visualize punctuation or view some human portraits made from data.
Design, in its many forms, is an iterative process. Take a look at all of the rejected ideas for the proposed Eiffel Tower in London. Some accounts, like Derek Watkins, share sketches as well as final products. Check out this one on Katie Ledecky.