While “big data” often connotes new opportunities for understanding the present, largely through the analysis of social media and search engine data, other newly available kinds of rich data sources create huge possibilities for reimagining the past. In recent years, millions of previously difficult-to-access documents and massive archival data structures have become widely available to scholars of human history and the general public. The project on Big Data and Historical Social Science brings together researchers across a range of disciplines, methods, and research strategies to explore the intersection of classical historical and social science problems and big data. How can access to new kinds of historical data, and new capacities to manipulate and analyze them, allow scholars to address historical questions in new ways?
In order to explore how scholars working on different aspects of a historical puzzle could collaboratively mobilize diverse datasets and data structures, participants established demonstration projects to focus on particular historical eras and questions. The first project is on "race" in the Americas in the period between the Reconstruction era and the civil rights movement (1877–1965). For this and future demonstration projects, the group will deploy techniques for “nesting” data—that is, utilizing temporal and spatial tools to understand changing data structures across time and levels of analysis—and for “linking” data—networking different kinds of data to provide a comprehensive picture and more thorough explanations of historical continuities and changes.