Browsing by Subject "research data management"

Now showing 1 - 2 of 2
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    Open Access
    Archiving South African digital research data: How ready are we?
    (2016) Koopman, Margaret M; de Jager, Karin
    Abstract Digital data archiving and research data management have become increasingly important for institutions in South Africa, particularly after the announcement by the National Research Foundation, one of the principal South African academic research funders, recommending these actions for the research that they fund. A case study undertaken during the latter half of 2014, among the biological sciences researchers at a South African university, explored the state of data management and archiving at this institution and the readiness of researchers to engage with sharing their digital research data through repositories. It was found that while some researchers were already engaged with digital data archiving in repositories, neither researchers nor the university had implemented systematic research data management.
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    Open Access
    Readiness for research data management in the life sciences at the University of the Witwatersrand
    (2022) Potgieter, Salomé; Kahn, Michelle
    Because of the importance of Research Data Management (RDM) in the life sciences, where vast amounts of research data in different complex formats are being produced, this study aimed to assess the state of RDM readiness in the life sciences at Wits to ascertain what support is needed with regards to RDM. In order to achieve the aim, the current RDM practices and needs of researchers, as well as the challenges they face, were investigated. The Jisc Research Data Lifecycle (Jisc, 2021a) was used to guide the literature review, frame data collection, analyse data and advise on some of the main findings and recommendations. A mixed methods approach and an explanatory sequential design were used to achieve the research objectives. For the quantitative phase of research, an online questionnaire was used to collect data. As the total target population (282) was not big, a census was conducted. The questionnaire was administered using SurveyMonkey software. During the qualitative part of the research, semi-structured interviews were used to explain the quantitative results. Five participants were purposively sampled to take part in interviews. The statistical package, MS Excel, was used to analyse quantitative data whilst qualitative data were analysed by thematic analysis. The study showed that life sciences researchers at Wits have adopted many RDM practices, and researchers are increasingly becoming aware of the importance of the openness of data. However, they are dealing with similar RDM issues as their peers worldwide. Results highlighted challenges of, amongst others, the lack of an RDM policy as well as the lack of, or unawareness of, appropriate RDM training and support at Wits. As formal implementation of RDM still needs to take place at Wits, it is recommended that Wits puts an RDM policy in place, followed by suitable RDM infrastructure and awareness making of current services.