Living Multiples: How Large-scale Scientific Data-mining Pursues Identity and Differences

Abstract

This article responds to two problems confronting social and human sciences: how to relate to digital data, inasmuch as it challenges established social science methods; and how to relate to life sciences, insofar as they produce knowledge that impinges on our own ways of knowing. In a case study of proteomics, we explore how digital devices grapple with large-scale multiples – of molecules, databases, machines and people. We analyse one particular visual device, a cluster-heatmap, produced by scientists by mining data from a large number of experiments on human blood plasma proteins. These proteins make up a myriad multiple whose identity shifts in many ways. Rather than displaying data about proteins, the heatmap constructs a view of the differences and similarities between experiments. We find this attempt to construct a view on many things at once instructive in thinking about multiples more generally. Instead of flattening molecular ‘life itself’, this visual device superimposes layers of digital devices and techniques from a wide variety of disciplines. This layering suggests a different way of relating to the life sciences more generally: rather than what they know, how they know might be of use to social and human sciences when attending to multiplicities.