There is growing interest in open research, including open data, with many proven benefits for the research community and society as a whole. Making data collected through specific projects open can increase the value of research projects by allowing for the replication of the findings, and presenting the option of additional secondary explorations of the data. Sharing data openly requires many considerations for researchers to ensure that ethical and privacy constraints are maintained. The data sharing process involves various steps in order to make the data open access in line with FAIR principles. These include data cleaning, conducting quality assessments, pseudonymisation, and data description.
This datahub initiative serves as a learning experience to document the process of sharing quantitative public health data collected through household- and health facility-level surveys. The purpose of the sharing is to make the data available for additional analyses beyond what was proposed in the original protocol. We rely on two primary datasets generated in the course of CREDO-Maternity project in Lubumbashi during the COVID-19 pandemic. The first contains data about pregnancy, care seeking and health outcomes as well as awareness of and perceptions towards COVID-19 in 600 households. The second contains data about births and women’s satisfaction with care received during the COVID-19 pandemic in health facilities across Lubumbashi
Started in January 2022 under CREDO-Maternity project on “Perception des services de santé et la qualité des soins de santé de la mère, du nouveau-né et de l’enfant dans le contexte particulier de l’épidémie de la COVID-19" - Lubumbashi
Pseudonymised dataset on public data repository, with accompanying metadata files (in preparation)
Sharing of experience: Practical guidance on making quantitative data publicly available
Peer-reviewed publication (to be confirmed)