Big Data and the Collective Turn in Biomedicine. How Should We Analyze Post-genomic Practices?


  • Alberto Cambrosio McGill University
  • Pascale Bourret Aix-Marseille Université, UMR SESSTIM
  • Vololona Rabeharisoa Mines - ParisTech
  • Michel Callon Mines - ParisTech



big data, network analysis, post-genomic medicine, bio-clinical collectives, actor-network theory


We presently witness a profound transformation of the configuration of biomedical practices, as characterized by an increasingly collective dimension, and by a growing reliance on disruptive technologies that generate large amounts of data. We also witness a proliferation of biomedical databases, often freely accessible on the Web, which can be easily analyzed thanks to network analysis software. In this position paper we discuss how science and technology studies (S&TS) may cope with these developments. In particular, we examine a number of shortcomings of the notion of networks, namely those concerning: (a) the relation between agency and structural analysis; (b) the distinction between network clusters and collectives; (c) the (ac)counting strategies that fuel the networking approach; and (d) the privileged status ascribed to textual documents. This will lead us to reframe the question of the relations between S&TS and biomedical scientists, as big data offer an interesting opportunity for developing new modes of cooperation between the social and the life sciences, while avoiding the dichotomies – between the social and the cognitive, or between texts and practices – that S&TS has successfully managed to discard.




How to Cite

Cambrosio, A., Bourret, P., Rabeharisoa, V., & Callon, M. (2014). Big Data and the Collective Turn in Biomedicine. How Should We Analyze Post-genomic Practices?. Tecnoscienza – Italian Journal of Science & Technology Studies, 5(1), 11–42.