Rethinking Empirical Social Science

While Big Data – the vast amounts of digital information generated, accumulated and stored in myriad databases and repositories, both online and offline – does present specific challenges to the geography discipline, I would suggest that it also calls for interdisciplinary approaches perhaps more than ever. There are of course many different rationales for interdisciplinarity but in the case of Big Data I will attend to two. First, the distributed relations and entanglements of ownership and expertise that make up Big Data call not only for interdisciplinary approaches but also cross- sectoral engagements between the social sciences, industry, government and business. And second, the ontological and epistemological consequences of methods that take up Big Data cut across disciplines and provide an opportunity for collaboration on the underlying theoretical propositions as well as the vexed political questions of data privacy, rights, ethics and ownership.

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All of these arguments for interdisciplinarity and collaboration are not a call for turning social scientists into statisticians or computer scientists, but for ‘socialising’ what could otherwise become a positivist science of individuals and societies or lead to re-inscribing a division between quantitative and qualitative methods. Retreating and engaging in internal debates within social science disciplines cannot achieve this, as Savage and Burrows (2007) also warn. Instead, it means to explore methods of doing immersive interdisciplinary data work by innovatively, critically and reflexively engaging with new forms of data. This calls for experimenting with various data sources and techniques, innovating methods, and working with researchers in computing and other sciences.

Dialogues in Human Geography. November 2013 vol. 3 no. 3 268-273

There’s a pre-print available here.