The use and reuse of open data in low resource settings

Prof Brian Rappert, Michelle Wilmers, Dr Louise Bezuidenhout and Prof Cheryl Hodgkinson-Williams at the Centre for Innovation in Learning and Teaching, University of Cape Town

Earlier this year, the ROER4D Hub team invited Dr Louise Bezuidenhout (University of Exeter and University of Witwatersrand) and Prof Brian Rappert (University of Exeter) to present on a project “Beyond the Digital Divide: Sharing Data Across Developing and Developed Data” that is investigating how scientists in African countries use online resources and open data, and what factors constrain or encourage engagement with openness. In a follow-up interview, Sukaina Walji spoke to Louise about assumptions made about how scientists engage with open data, the practicalities for use of open data, understandings of openness, and ways in which scientists in developing contexts might be encouraged to participate in Open Science practices.

As ROER4D has recently launched the ROER4D Open Data Initiative we are interested in connecting with and learning from projects that engage with open data in developing contexts. The research undertaken by Louise and her colleagues is helping shed some light on some of the actual practices and circumstances that affect researchers who could potentially work with and benefit from open data and engage in Open Science practices.

Assumptions made about the use of open data

Louise’s research seeks to unpack key assumptions about how scientists undertaking biochemistry research in low resourced labs might use data. There is often an assumption made in open data discussions that the access to data equates with the ability to reuse it, yet Louise and the team questioned this “egalitarian assumption”. Such assumptions regarding use of open data are made in high income countries and driven forward from professionals who work in relatively high resource contexts. whereby more data available online lead to more re-use. However in a low resource context such as a poorly resourced science lab, access to open data does not necessarily mean that scientists would be able to use it.

Louise uses the term ‘data engagement’ covering generation, storage, dissemination and reusing thus engaging with online data as both producer and consumer. Louise’s research found that scientists in resource constrained African labs were reluctant to engage with open data practices not only because it was an additional thing to do, but spoke to very real concerns that they would be “scooped” – a concern that has been raised elsewhere but not as prominently as in these labs.

Underlying these concerns was a more basic set of issues: the scientists interviewed experienced many challenges in simply doing science. This was a result of a reliance on older equipment, practices necessitating sharing equipment between scientists, lack of access to research funds, water controls and other small systemic issues that together contribute to a slowing of research in developing countries. Yet these issues are seen as part and parcel of the environment. In these circumstances taking an ‘agile approach’ to open research and open data practices is unfeasible. Such constraints applied both to releasing data and also affected researchers ability to reuse data, despite having internet access and speciously not being on the wrong side of “digital divide”.

Understandings of openness

Another assumption is that all scientists have a similar understanding of what openness is. Louise mentioned that in comparison with understandings of openness in UK labs, her work with scientists in Africa showed very different understandings of openness. The research found that “open anything” was difficult to talk about, with “open data” an uncomfortable term for many. “Open Science” is often used as blanket term, but the term ‘Open Science’ was not well understood.

Researchers did comment on (not) having access to journal articles and open access issues with unhappiness about restricted access. However as many scientists needed access to niche journals, open access issues per se were not at the forefront. Similarly there was little awareness of altmetrics or social academic repositories such as

A capability approach to contextualise data engagement

Taking a capability lens to articulate to findings, the research team argue for a recontextualisation of the whole data engagement process. Rather than a straight line between access to resources and use in research, a capability approach identifies different environmental issues and the “conversion factors” to enable data engagement.

Louise contends that high income countries need to recognise these conversion factors while scientists in low income countries need to be comfortable to talk about constraints in their environment. Possible solutions include the availability of microcredit to deal with ongoing environmental issues and that giving researchers agency to solve some of these factors could see a massive surge in the use of open data.

In terms of awareness of open data and open access, the role of librarians is important. Scientists are not aware of what Open Science, open data and open access means and how to use open repositories. Issues about ownership needs to be addressed from contextual rather than a developed world perspective.

For more information on this project and research see Louise’s blog:

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