Beyond Data Driven Social Science: Researching Big Data Assemblages

The expansion of “dataification” of society makes available to social researchers a huge amount of data. A first epistemological consequence of the passage from data scarce to data intensive societies has been the re-emergence of data driven science. But the opposition of data-driven versus hypothesis-driven research and the focus on analytics and tools to handle new data it leaves in background the fact that data do not exist by themselves, being rather the outcome of a very complex process. There is therefore the need to develop more research about not only the technical addresses which guide new data research, but also about the cognitive, normative and political imperatives that shape the background knowledge that it is used to make sense of these new data. As new Big Data assemblages are increasingly coming to shape government policy, commercial practice and popular representations of the social world, it is progressively recognized the need to think critically about their production and consumption. The better equipped scientists to carry this job out are social scientists, who have in their epistemological traditions the most critical approaches to data, reality and knowledge.