20 May 2021
The May session of Big Data and the Historian’s Craft shifts our attention to data science and methodological reflections. Text analysis, GIS, network analysis, and machine learning have become part and parcel of digital methods training.
However, historians used cadastral surveys, census records, ledgers, maps, and genealogies in their research long before the digital turn. The long view should help us better understand what distinguishes our current paradigm from previous attempts to incorporate quantitative methods and information visualization strategies into historical research. Nonetheless, most digital history projects at the moment utilize sub-gigabyte digital representations of primary sources originally in print form.
What changes when digital history scales up to petabyte-scale databases distributed across multiple servers? Will the goal be to account for “everything” or to create subsets or samples? Will the historical profession turn into an extension of data science? Or will some aspects of the historian’s craft remain unchanged despite the advent of big data?