When more data means better results: Abundance and scarcity in research collaborations in epigenetics. (March 2020)

• Record Type: Journal Article
• Authors: Pinel, Clémence
• Other Names: Dubois Michel guest-editor.; Louvel Séverine guest-editor.; Rial-Sebbag Emmanuelle guest-editor.
• Is Part Of: Social science information. Volume 59:Number 1(2020:Mar.)
• Page Start: 35
• Page End: 58
• Publication Date: 2020-03
• Subjects: asset -- data -- epigenetics -- rent -- research consortium -- scientific collaborations -- value; actifs -- collaborations scientifiques -- consortium de recherche -- données -- épigénétique -- rente -- valeur; Social sciences -- Periodicals; Social history -- Periodicals; Technology and civilization -- Periodicals; Electronic journals; 300.5
• DOI: 10.1177/0539018419895456
• Languages: English
• ISSNs: 0539-0184

Abstract

Drawing upon ethnographic findings from an epigenetics research laboratory in the United Kingdom, this article explores practices of research collaborations in the field of epigenetics, and epigenomics research consortia in particular. I demonstrate that research consortia are key scientific infrastructures that enable the aggregation of masses of data deemed necessary for the production of results and the fostering of epistemic value. Building on Science and Technology Studies (STS) scholarship on value production, and the concept of asset, I show that the production of valuable research within epigenomics research consortia rests on the active organisation and management of abundance and scarcity. It involves shaping and standardising the masses of data gathered in consortia, while it also entails research teams enclosing their data within their laboratories' walls. As they do so, research teams construct data into scarce and monopolised assets, which they can put to productive use in collaborative endeavours against a revenue. In addition to contributing empirical and critical insights into the ways epigenetics knowledge is formed and negotiated in specific research contexts, this article offers conceptual tools to examine and problematise knowledge production practices in data-intensive research more broadly. In particular, it points out that while contemporary big biology is marked by the generalised imperative to 'share' data and 'open' science, collaborative endeavours within research consortia are built around forms of exclusions.