Publication Date

March 1, 2012

Perspectives Section

From the Executive Director

AHA Topic

Career Paths

According to this morning’sNew York Times (February 12, 2012), we have entered “The Age of Big Data.” Having spent some time working through the meaning and implications of “Big History”—and emerging with considerable admiration for the ambitions of those who teach it—I knew the article would require at least two readings. On a second read, my first instinct proved true: there is something here for historians. Maybe even something Big.

“Big Data” refers to the zillions of pieces of information that traverse the internet, flowing across the full range of human and nonhuman activity. In this sense it has some affinity with Big History, which begins from the principle that our engagement with the past knows no boundaries. So too Big Data. Consider just a few of its flows: social media conversations; transactions at the retail and wholesale levels; sensors monitoring movement of all sorts across the earth; climate; curriculums and student performance; financial data of any kind; sports statistics; the list goes on and on and on….

But (and this is what matters to historians): the data are useless until we have them organized into conceptual frameworks able to answer useful questions. Decontextualized data are frequently offered to potential users who quite reasonably assume that understanding patterns of behavior in the past can help to predict future activity. Police forces, for instance, refer to “historical arrest patterns” as one piece of an algorithm generating predictions useful to assigning priorities. A good historian, however, knows never to assume continuity, seminar debates over the dynamics of continuity and change being among the clichés of graduate education.

Another example.The Times article describes a United Nations initiative now exploring ways of mobilizing social media and texting content to serve as “digital early-warning signals” of economic or public health crises. Decoding these signals is historical work: untangling their true meanings requires proper analysis of their context. To study these signals is to study change—to figure out how change happens—which is what historians do best.

I am not suggesting that we all become statisticians. But data from the past—even the immediate past—are neither straightforward substance nor transparent material. Organizing piles of scraps of information into a coherent argument is no easy task. This is why it takes a long time to research and write a good history dissertation. Whether or not we have a facility with numbers, we are good at asking questions and analyzing evidence that by its nature generates many variables at once. And because we look for stories—for ways of synthesizing diverse strands into narrative themes—we usually look for interactions among variables that to other eyes might not seem related. By casting our insights into the form of narratives, we also make them more accessible than multivariate regression analyses could ever be—and arguably more amenable to uncertainty and ambiguity. I have little doubt that people asking big questions of Big Data would benefit from collaboration with the qualitative and interpretive perspectives historians bring to this kind of enterprise. It is our task to prepare our students for such options, and to convince those beyond the community of historians that we have something to contribute.

Graduate programs might begin thinking more intentionally about the implications of the digital environment as it pertains to our discipline. This includes the potential for new kinds of collaboration that could even be explored experimentally in graduate school. Why not think about joining the historian’s analytical and narrative skills to the statistician’s methods of organization and analysis? Or the historian’s facility with sifting and contextualizing information to the computer scientist’s (or marketing professional’s) ability to generate and process data?

Writing recently for the U.S. Intellectual History blog, graduate student L. D. Burnett recalled leaving the 2012 AHA annual meeting “desperate to hear something that would give me a modicum of hope as I look ahead at what appears to me and many others to be an absolutely abysmal academic job market.” Big Data is one of many fields that might give Burnett hope that interesting and useful things await beyond the academy gate; and even beyond the broad range of public history arenas that already exist. The AHA is committed to working with history departments to identify those opportunities and help provide our students with the resources to explore them. Stay tuned.

is the executive director of the AHA.

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