Research Data Management and Scientific Evidence: A Strategic Imperative for SDGs

Abstract

Scientific evidence comprises Data, Information and Knowledge (DIK) often presented in a pyramidal structure. Data are the foundation base of the pyramid, followed by the information layer and the knowledge layer at the top. Data are rudimentary and expand into information and knowledge—the DIK pyramid— and also constitute scientific evidence. Such evidence is critical for demonstrating prospects, best practices and successful development models. The Internet and the evolution of the Web have resulted in easily discernible data that serve as scientific evidence in the form of big data. Transformation of the African continent through the 17 Sustainable Development Goals (SDGs) rests on the availability of scientific data. Data are not a panacea for societal problems but data science can nevertheless open up possibilities for innovations that could help fight hunger, poverty, inequalities and underdevelopment. There is also a huge potential for big data to serve as evidence for successes and failures of the SDGs. However, without its proper creation, planning, verification, storage, security and organisation; big data cannot be used appropriately. This is where Research Data Management (RDM) adds value, mainly because RDM is concerned with planning and organisation of data in the entire research cycle, including the dissemination and archiving of results. This chapter draws on examples from Kenya, Malawi and South Africa to analyse RDM as a strategic imperative for scientific evidence in the transformation of Africa through the SDGs, with a specific reference to SDG 4 on the quality of education.