Research data management practices in climate change research: A quantitative study of Southern African Science Service Centre for Climate Change and Adaptive Land Management, Namibia

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The purpose of this study was to assess how research data is managed at the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) in order to increase the understanding of current research data management (RDM) practices and inform future RDM procedures at the facility. The research objectives of the study were to investigate the RDM practices of climate change researchers affiliated with SASSCAL and to explore the challenges if any, that these researchers face with respect to RDM. The study was underpinned by the Digital Curation Centre's Curation Lifecycle Model (Higgins, 2008). The study employed a postpositivist worldview with a quantitative research approach that enabled the researcher to collect and analyse quantitative data to achieve the study objectives. A census approach was used to select all climate change researchers affiliated with SASSCAL. Data were collected using an online questionnaire created using Google Forms. The research results were analysed using Excel, and the results were presented through descriptive statistics. The study findings established that climate change researchers are managing certain RDM practices well, such as using multiple sites for data storage and backups, appraising data for long-term preservation, naming files and folders conventionally, as well as participating in some aspects of data sharing. However, the researchers exhibited some questionable RDM practices such as using poor long-term data storage options, and metadata and displaying a lack of overall data management planning on research projects. The results show that there is no data appraisal and selection policy at SASSCAL and a lack of awareness of RDM policies among researchers. Among the recommendations of the study are: the implementation of an RDM policy at SASSCAL; international collaboration with other research institutes to tap into best practices on RDM; RDM training; creating awareness of good RDM practices; and mandatory data management planning.