Pinel Clémence
Centre for Medical Science and Technology Studies, University of Copenhagen, Denmark.
Soc Sci Inf (Paris). 2020 Mar 1;59(1):35-58. doi: 10.1177/0539018419895456. Epub 2020 Jan 16.
Drawing upon ethnographic findings from an epigenetics research laboratory in the United Kingdom, this paper 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 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 paper 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.
基于对英国一个表观遗传学研究实验室的人种志研究结果,本文探讨了表观遗传学领域的研究合作实践,尤其是表观基因组学研究联盟。我证明研究联盟是关键的科学基础设施,能够聚集大量被认为是产生研究结果和培育认知价值所必需的数据。基于科学技术与社会(STS)关于价值生产的学术研究以及资产概念,我表明表观基因组学研究联盟内有价值研究的产生依赖于对丰富性和稀缺性的积极组织与管理。这涉及对联盟中收集的大量数据进行塑造和标准化,同时也要求研究团队将其数据封闭在实验室范围内。当他们这样做时,研究团队将数据构建成稀缺且被垄断的资产,这些资产可用于合作项目中以获取收益。除了对表观遗传学知识在特定研究背景下如何形成和协商提供实证和批判性见解外,本文还提供了概念工具,以更广泛地审视和质疑数据密集型研究中的知识生产实践。特别是,它指出虽然当代大型生物学的特点是普遍要求“共享”数据和“开放”科学,但研究联盟内的合作项目却是围绕着各种形式的排他性构建的。