Digging into Data white paper : Trading Consequences

Abstract

Scholars interested in nineteenth century global economic history face a voluminous historical record. Conventional approaches to primary source research on the economic and environmental implications of globalised commodity flows typically restrict researchers to specific locations or a small handful of commodities. By taking advantage of cutting edge computational tools, the project was able to address much larger data sets for historical research, and thereby provides historians with the means to develop new data driven research questions. In particular, this project has demonstrated that text mining techniques applied to tens of thousands of documents about nineteenth century commodity trading can yield a novel understanding of how economic forces connected distant places all over the globe and how efforts to generate wealth from natural resources impacted on local environments. The large scale findings that result from the application of these new methodologies would be barely feasible using conventional research methods. Moreover, the project vividly demonstrates how the digital humanities can benefit from transdisciplinary collaboration between humanists, computational linguists and information visualisation experts