Dr. Mark Ravina recently authored a post on Digital Humanities Now titled “Smooth and Rough on the Highways of France.” Named an “Editor’s Choice,” the post examines how quantitative methods, in this case data visualization, can assist in posing new historical questions. Below is an excerpt from the article, which can be found in full here.

One way to conceptualize this complementarity [between social science and humanistic methods] is John Tukey’s observation that “data = smooth + rough,” or, in more common parlance, quantitative analysis seeks to separate patterns and outliers. In a traditional social science perspective, the focus is on the “smooth,” or the formal model, and the corresponding ability to make broad generalizations. Historians, by contrast, often write acclaimed books and articles on the “rough,” single exceptional cases. These approaches are superficially opposite, but there is an underlying symbiosis: we need to find the pattern before we can find the outliers.