pubmed.ncbi.nlm.nih.gov

Data sharing and data governance in sub-Saharan Africa: Perspectives from researchers and scientists engaged in data-intensive research - PubMed

  • ️Invalid Date

Data sharing and data governance in sub-Saharan Africa: Perspectives from researchers and scientists engaged in data-intensive research

Siti M Kabanda et al. S Afr J Sci. 2023 May-Jun.

Abstract

The data ecosystem is complex and involves multiple stakeholders. Researchers and scientists engaging in data-intensive research collect, analyse, store, manage and share large volumes of data. Consequently, capturing researchers' and scientists' views from multidisciplinary fields on data use, sharing and governance adds an important African perspective to emerging debates. We conducted a descriptive cross-sectional survey and received 160 responses from researchers and scientists representing 43 sub-Saharan African countries. Whilst most respondents were satisfied with institutional data storage processes, 40% indicated that their organisations or institutions did not have a formally established process for storing data beyond the life cycle of the project. Willingness to share data was generally high, but increased when data privacy was ensured. Robust governance frameworks increased the willingness to share, as did the regulation of access to data on shared platforms. Incentivising data sharing remains controversial. Respondents were satisfied with exchanging their data for co-authorship on publications (89.4%) and collaboration on projects (77.6%). However, respondents were split almost equally in terms of sharing their data for commercial gain. Regarding the process of managing data, 40.6% indicated that their organisations do not provide training on best practices for data management. This could be related to a lack of resources, chronic institutional under-investment, and suboptimal research training and mentorship in sub-Saharan Africa. The sustainability of data sharing may require ethical incentive structures to further encourage researchers and scientists. Tangible infrastructure to facilitate such sharing is a prerequisite. Capacity development in data governance for researchers and scientists is sorely needed.

Significance: Data sharing is necessary to advance science, yet there are many constraints. In this study, we explored factors that promote a willingness to share, as well as constraining factors. Seeking potential solutions to improve data sharing is a scientific and ethical imperative. The standardisation of basic data sharing and data transfer agreements, and the development of a Data Access Committee will strengthen data governance and facilitate responsible data sharing in sub-Saharan Africa. Funders, institutions, researchers and scientists ought to jointly contribute to fair and equitable data use and sharing during and beyond the life cycle of research projects.

Keywords: big data; data governance; data sharing; data transfer agreements; researchers; scientists; sub-Saharan Africa.

PubMed Disclaimer

Conflict of interest statement

Competing interests We have no competing interests to declare.

Figures

Figure 1:
Figure 1:

Number of respondents across the different sub-Saharan African countries.

Figure 2:
Figure 2:

Perspectives on the reuse of data.

Figure 3:
Figure 3:

Satisfaction with data practices.

Figure 4:
Figure 4:

Data-sharing practices.

Figure 5:
Figure 5:

Reasons for not making data electronically available.

Similar articles

Cited by

References

    1. Guo H, Hackmann H, Gong K. Big data in support of the Sustainable Development Goals: A celebration of the establishment of the International Research Center of Big Data for Sustainable Development Goals (CBAS). Big Earth Data. 2021;5(3):259–262. 10.1080/20964471.2021.1962621 - DOI
    1. Hassani H, Huang X, MacFeely S, Entezarian MR. Big Data and the United Nations Sustainable Development Goals (UN SDGs) at a glance. Big Data Cogn Comput. 2021;5(3), Art. #28. 10.3390/bdcc5030028 - DOI
    1. De Mauro A, Greco M, Grimaldi M. A. formal definition of Big Data based on its essential features. Libr Rev. 2016;65(3):122–135. 10.1108/LR-06-2015-0061 - DOI
    1. De Cnudde S, Martens D. Loyal to your city? A data mining analysis of a public service loyalty program. Decis Support Syst. 2015;73:74–84. 10.1016/j.dss.2015.03.004 - DOI
    1. Mallappallil M, Sabu J, Gruessner A, Salifu M. A review of big data and medical research. SAGE Open Med. 2020;8, Art. #2050312120934839. 10.1177/2050312120934839 - DOI - PMC - PubMed