What Difference Does Quantity Make? On the Epistemology of Big Data Biology
Leonelli, Sabina
Date: 2014
Publisher
SAGE
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Abstract
Is Big Data science a whole new way of doing research? And 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, but rather in (1) the prominence and status acquired by data as commodity and ...
Is Big Data science a whole new way of doing research? And 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, but rather in (1) the prominence and status acquired by data as commodity and recognised output, both
within and outside of the scientific community and (2) the methods, infrastructures, technologies, skills and knowledge
developed to handle data. These developments generate the impression that data-intensive research is a new mode of
doing science, with its own epistemology and norms. To assess this claim, one needs to consider the ways in which data
are actually disseminated and used to generate knowledge. Accordingly, this article 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 prominent infrastructures set up to organise and interpret such
data and examine the wealth and diversity of expertise, resources and conceptual scaffolding that such databases draw
upon. This illuminates some of the conditions under which Big Data needs to be curated to support processes of
discovery across biological subfields, which in turn highlights the difficulties caused by the lack of adequate curation for
the vast majority of data in the life sciences. In closing, I reflect on the difference that data quantity is making to
contemporary biology, the methodological and epistemic challenges of identifying and analysing data given these developments,
and the opportunities and worries associated with Big Data discourse and methods.
Social and Political Sciences, Philosophy, and Anthropology
Faculty of Humanities, Arts and Social Sciences
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