Mzuzu University Digital Repository

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

Show simple item record

dc.contributor.author Kapondera, Sellina
dc.contributor.author Bitso, Constance
dc.contributor.author Makori, Elisha
dc.date.accessioned 2022-07-19T17:22:15Z
dc.date.available 2022-07-19T17:22:15Z
dc.date.issued 2020
dc.identifier.citation Kapondera, S., Bitso, C. & Makori, E. (2020). Research Data Management and Scientific Evidence: A Strategic Imperative for SDGs. Africa and the Sustainable Development Goals, 103-112. https://doi.org/10.1007/978-3-030-14857-7_10 en_US
dc.identifier.uri https://doi.org/10.1007/978-3-030-14857-7_10
dc.identifier.uri https://www.researchgate.net/publication/333784634_Research_Data_Management_and_Scientific_Evidence_A_Strategic_Imperative_for_SDGs
dc.identifier.uri 192.168.2.8:8080/xmlui/handle/123456789/282
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher Springer en_US
dc.subject Quality education en_US
dc.subject Africa en_US
dc.title Research Data Management and Scientific Evidence: A Strategic Imperative for SDGs en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search MzuniDR


Advanced Search

Browse

My Account