Technology Transfer and True Transformation: Implications for Open Data

Abstract

When considering the “openness” of data it is unsurprising that most conversations focus on the online environment – how data is collated, moved and recombined for multiple purposes. Nonetheless, it is important to recognize that the movements online are only part of the data lifecycle. Indeed, considering where and how data are created – namely, the research setting – are of key importance to Open Data initiatives. In particular, such insights offer key understandings of how and why scientists engage with in practices of openness, and how data transitions from personal control to public ownership.

This paper examines research settings in low/middle-income countries (LMIC) to better understand how resource limitations influence Open Data buy-in. Using empirical fieldwork in Kenyan and South African laboratories it draws attention to some key issues currently overlooked in Open Data discussions. First, that many of the hesitations raised by the scientists about sharing data were as much tied to the speed of their research as to any other factor. Thus, it would seem that the longer it takes for individual scientists to create data, the more hesitant they are about sharing it. Second, that the pace of research is a multifaceted bind involving many different challenges relating to laboratory equipment and infrastructure. Indeed, it is unlikely that one single solution (such as equipment donation) will ameliorate these “binds of pace”. Third, that these “binds of pace” were used by the scientists to construct “narratives of exclusion” through which they remove themselves from responsibility for data sharing.

Using an adapted model of technology first proposed by Elihu Gerson, the paper then offers key ways in which these critical “binds of pace” can be addressed in Open Data discourse. In particular, it calls for an expanded understanding of laboratory equipment and research speed to include all aspects of the research environment. It also advocates for better engagement with LMIC scientists regarding these challenges and the adoption of frugal/responsible design principles in future Open Data initiatives.