Data Commoning in the Life Sciences

Datafication is driving organizations to invest in data commons not only to share the costs of data generation, analysis, and curation; but more importantly, to realize synergies in precompetitive research collaborations where private and public motives interact (i.e., semicommons). The fanfare surrounding datafication often hails the sophisticated algorithms used to develop large quantities of data toward greater insight, naïvely assuming that more data equals better data. Yet, for datafication in general and precompetitive research specifically, less attention is awarded to what actually constitutes data and evidence in the first place—that is, to its genesis, construction, and interpretation by heterogeneous scientific and commercial entities. We present the case of Open Targets, a precompetitive collaboration in the life sciences, where publicly funded research, nonprofit foundations, and for-profit pharma collaborate to generate and share data in genomics, proteomics, and bioinformatics. We theorize about the process of data commoning, a political activity in the semicommons where data are created, evidential value is assembled, and scientific meaning converges as data travels, or journeys across creators, validators, and users. Our findings highlight the effects of relational dynamics and political nature of data journeys: why these dynamics form, how they are manifest in a precompetitive semicommons, and what implications this can have for the mobility of data as shared, public good.