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As with any high fashion, the beauty and horror of “big data” 1 is in the eye of the beholder. The ques-tion that prompted the present symposium—“Are formal theory, causal inference, and big data contradictory trends in political science?”—is representative of the concerns that big data has raised in political science. Indeed, this is representative of discussions underway in every area of social science about how big data interacts with existing modes of inquiry as well as its potential benefits (Lazer et al. 2009; Varian 2014) and potential pitfalls (boyd and Crawford 2012; Lazer et al. 2014).

A review of these discussions does not yield any consensus on even what is meant by the term “big data.” For us, the concept is broad and simultaneously captures several ideas. For us, the intuitive criterion—“lots of data”—is both unnecessary and insufficient. When referring to data qua data,“big” is defined relative to the …