Assembling Biomedical Big Data
© The Author(s) 2018
Reason for embargo
Under embargo until 1 February 2021 in compliance with publisher policy
This chapter examines the challenges involved in disseminating, integrating and analyzing large datasets collected within both clinical and research settings. I highlight the technical, ethical and epistemic concerns underlying attempts to portray and use Big Data as revolutionary tools for producing biomedical knowledge and related interventions. When bringing together data collected on human subjects with data collected from other organisms, significant differences in the experimental cultures of biologists and clinicians emerge, which if left unchallenged risk to compromise the quality and validity of large scale, cross-species data integration. The study of data integration calls attention to the fragmented, localized and inherently translational nature of biomedical research, and the challenges underlying the assemblage and interpretation of big data in this domain.
The empirical research for that paper was funded by the UK Economic and Social Research Council, as part of the ESRC Centre for Genomics in Society; the research used to reframe and update that work was funded by the European Research Council grant award 335925 (“The Epistemology of Data-Intensive Science”).
This is the author accepted manuscript. The final version is available from Palgrave via the DOI in this record
In: Handbook for Biology and Society, edited by Meloni M., Cromby J., Fitzgerald D., and Lloyd S, pp. 317-337