The locus of legitimate interpretation in Big Data sciences: Lessons for computational social science from -omic biology and high-energy physics

Abstract

This paper argues that analyses of the ways in which Big Data has been enacted in other academic disciplines can provide us with concepts that will help understand the application of Big Data to social questions. We use examples drawn from our Science and Technology Studies (STS) analyses of-omic biology and high energy physics to demonstrate the utility of three theoretical concepts: (i) primary and secondary inscriptions, (ii) crafted and found data, and (iii) the locus of legitimate interpretation. These help us to show how the histories, organisational forms, and power dynamics of a field lead to different enactments of big data. The paper suggests that these concepts can be used to help us to understand the ways in which Big Data is being enacted in the domain of the social sciences, and to outline in general terms the ways in which this enactment might be different to that which we have observed in the 'hard' sciences. We contend that the locus of legitimate interpretation of Big Data biology and physics is tightly delineated, found within the disciplinary institutions and cultures of these disciplines. We suggest that when using Big Data to make knowledge claims about 'the social' the locus of legitimate interpretation is more diffuse, with knowledge claims that are treated as being credible made from other disciplines, or even by those outside academia entirely.

Connective knowledge: what we need to know about other fields to ‘envision’ cross-disciplinary collaboration

“…From researchers in one field being misunderstood by others so that they become an 'appendix' to projects [57], performing 'service roles' , e.g. social scientists being asked to 'stuff envelopes' to 'being the general person for anything to do with people' [15], to the overestimation of what one knows or can know about other fields [49,61,3], to the side-lining of conceptual and theoretical contributions different disciplines can make [49,3] the variety of problems that unfold in the 'doing' of cross-disciplinary work as a result of what is 'not known' seems to tantalisingly lead to the conclusion that knowing more about something relating to other fields might be the solution.…”

“…Once we identify that cross-disciplinary collaboration constitutes the ideal vehicle for addressing much of what might be rationalised as an inevitable Of-knowledge deficit, then our aspiration to address gaps in knowledge look like knowledge of a far humbler kind. 3 In light of the concerns we have highlighted above, as well as the limited time that researchers have for extra-disciplinary learning, a practical agenda for 'knowing more' should focus on an enabling strategy where less is more.…”

“…That connective ' About-Knowledge' , rather than more sophisticated forms of extra-disciplinary 'Of-Knowledge' , might be more valuable for stimulating cross-disciplinary collaborative connections also finds support from other quarters. There is now a developing body of work that highlight fundamental misconceptions and stereotypical ideas about what researchers within non-home fields actually do [62] in ways that lead researchers to erroneously overlook and exclude particular domains for cross-disciplinary projects [2,49,3]. Addressing basic misconceptions about fields and specialisms-for example, that legal academics researchers are typically involved in 'litigating cases' [62], or wholly non-specified ideas about social science so that social scientists are seen as the 'people people' [49]-do not require much 'corrective' information beyond highlighting the richer range of research problem domains in which those disciplines are engaged, and the potential contributions that those fields can make to cross-disciplinary collaborations.…”

“…Or indeed, researchers come to believe that future studies 'is primarily about "prediction" and "forecasting" to the idea that future studies can be nothing more than "ungrounded speculation", because the future is inherently unknowable' ( [28], p. 24). This kind of knowledge deficit, about other fields, provides fertile ground for misconceptions about other specialisms, for actors exceeding their own field of expertise [3,61] and importantly, for missed opportunities for valuable and important collaborations by virtue of a failure to understand the value of, and expertise inherent within other fields and specialisms.…”

Analysing the role of virtualisation and visualisation on interdisciplinary knowledge exchange in stem cell research processes

“…This has led to an exponential increase in the volume and variety of biological data as well as substantial growth of the number and diversity of interdisciplinary collaborations. With this have come new ways of organising and valuing computational biological work, seen most clearly in the emergence of bioinformatics as a leading space for conducting this work (Lewis et al, 2016, Bartlett et al, 2018. Consortia or large scale projects are usually based on highly organised collaborations, undertaking scientific activities in a manufacturing-style environment with standard operating procedures and a great degree of automation, but often little room for creativity.…”