Analyzing and interpreting “imperfect” Big Data in the 1600s

Abstract

One of the characteristics of Big Data is that it often involves “imperfect” information. This paper examines the work of John Graunt (1620–1674) in the tabulation of diseases in London and the development of a life table using the “imperfect data” contained in London’s Bills of Mortality in the 1600s. London’s Bills of Mortality were Big Data for the 1600s, as they included information collected over time, the depth and accuracy of which improved gradually. The main shortcoming of the data available at the time was its nonuniform upkeep and the lack of depth of variables included at its outset. Due to these characteristics, it provides a perfect model for the examination of imperfect Big Data, as it has been analyzed, criticized, and interpreted repeatedly since the 1600s.