Data Visualization in Sociology by Kieran Healy and James Moody. (Annu. Rev. Sociol. 2014. 40:5.1–5.24, DOI: 10.1146/annurev-soc-071312-145551)
Abstract:
Visualizing data is central to social scientific work. Despite a promising early beginning, sociology has lagged in the use of visual tools. We review the history and current state of visualization in sociology. Using examples throughout, we discuss recent developments in ways of seeing raw data and presenting the results of statistical modeling. We make a general distinction between those methods and tools designed to help explore data sets and those designed to help present results to others. We argue that recent advances should be seen as part of a broader shift toward easier sharing of the code and data both between researchers and with wider publics, and we encourage practitioners and publishers to work toward a higher and more consistent standard for the graphical display of sociological insights.
A great review of data visualization in sociology. I was impressed by the author’s catching the context of John Maynard Keyes‘ remark about the “evils of the graphical method unsupported by tables of figures.”
In 1938, tables of figures reported actual data, not summaries. With a table of figures, another researcher could verify a graphic representation and/or re-use the data for their own work.
Perhaps journals could adopt a standing rule that no graphic representations are allowed in a publication unless and until the authors provide the data and processing steps necessary to reproduce the graphic. For public re-use.
The authors’ also make the point that for all the wealth of books on visualization and graphics, there is no cookbook that will enable a user to create a great graphic.
My suggestion in that regard is to collect visualizations that are widely thought to be “great” visualizations. Study the data and background of the visualization. Not so that you can copy the technique but in order to develop a sense for what “works” or doesn’t for visualization.
No guarantees but at a minimum, you will have experienced a large number of visualizations. That can’t hurt in your quest to create better visualizations.
I first saw this in a tweet by Christophe Lalanne.