Analysts underlying assumption seems to be that research data and work *should* be connected (for better science?) but because of these barriers (named in paper), they are not being connected or used as much as they should or could be. (“These costs, however small in comparison to research budgets, inhibited many of the research participants from engaging with these different platforms – thus missing many opportunities to profile and connect their research to that of others” (42).
Bezuidenhout et al. are strongest on their techno and macro levels of analysis but their nano and micro levels are wanting as it is hard to get a sense of who they were engaging (students? employees? faculty? administrators?) and also what exactly was involved in the “data engagement” that was being discussed. The concept of “data” was used in different valances (by them as well as the interlocutors) and that was not noted or analyzed. I think their use of “data” is largely to mean research outputs? But there is a conflation between open access and open data which are not the same thing. Authors also are conflating Open Data with Open Science which are also not the same thing. I would argue that this is more the “Open Data” movement rather than the maxim of OS (“OS understands democratizing science as increasing the amount of data available” p. 45).
There is also a missing aspect which is the contribution BACK into the online data platforms. Access appears to be a one-sided “use” of outputs of data but the paper doesn’t discuss the importance of circulation (with creation by / from African scholars as well).
There seems to be an underlying assumption that data sharing should be designed to be at a global scale: “clearly what is necessary is a global, coordinated, inter-disciplinary and multi-focused discussion on how to pull these diverse aspects together into a coherent approach.” (45) My own opinion is that data sharing can be valuable even within a very micro-research community, esp. if there is the ability to gain access to it or if it is archived and managed in a way that has the potential for it to be available to others in the future. I do not think data sharing needs to be automatically at a global scale. In fact, that is what is currently being done and it is problematically centralized by private Western players so I don’t think that is the solution.
I also question the assumption that because there are more people on the continent using their mobile phone that data sharing capabilities need to be built for the mobile phone (“The dominance of cellular phones on the African continent – in comparison to other ICTs – and their increasingly effective use in a wide range of financial and health-related applications should provide a focal point for OS initiatives on the continent – too many websites critical for data engagement are highly cumbersome for use on mobile devices”, pg 45). I think the question is *who* the data is for. Is it for lab based researchers? Are lab based researchers all using laptops at work? What functionalities are available on the laptop vs the mobile phone? These are the very “user-specific” contextual factors that should be considered. Who/when/where/why are people using their phones and who/when/where/why are African scientists using data sharing platforms?
