What Difference Does Quantity Make? On the Epistemology of Big Data in Biology
Thursday 20 February 2014, 14:15-15:15pm, Amphimax 414
This paper focuses the epistemological significance of big data within biology: is big data science a whole new way of doing research? Or, in other words: what difference does data quantity make to knowledge production strategies and their outputs? I argue that the novelty of big data science does not lie in the sheer quantity of data involved, though this certainly makes a difference to research methods and results. Rather, the novelty of big data science lies in (1) the prominence and status acquired by data as scientific commodity and recognised output; and (2) the methods, infrastructures, technologies and skills developed to handle (format, disseminate, retrieve, model and interpret) data. These developments generate the impression that data-intensive research is a new mode of doing science, with its own epistemology and norms. I claim that in order to understand and critically discuss this claim, we need to analyze the ways in which data are actually disseminated and used to generate knowledge, and use such empirical study to question what counts as data in the first place. Accordingly, the bulk of this paper reviews the development of sophisticated ways to disseminate, integrate and re-use data acquired on model organisms over the last three decades of work in experimental biology. I focus on online databases as a key infrastructure set up to organise and interpret such data; and on the diversity of expertise, resources and conceptual scaffolding that such databases draw upon in order to function well, including the ‘Open Data’ movement which is currently playing an important role in articulating the incentives for sharing scientific data in the first place. This case study illuminates some of the conditions under which the evidential value of data posted online is assessed and interpreted by researchers wishing to use those data to foster discovery, which in turn informs a philosophical analysis of what counts as data in the first place, and how data relate to knowledge production. In my conclusions, I reflect on the difference that data quantity is making in contemporary biological research, the methodological and epistemic challenges of identifying and analyzing data given these developments, and the opportunities and worries associated to big data discourse and methods.