Research data management

Research data management (RDM) is essential for all researchers, as data is central to modern scientific discovery (Tenopir et al., 2020). RDM involves actively and continuously managing data throughout its entire lifecycle (Cox & Pinfield, 2014; Wilms et al., 2020). Good RDM supports knowledge discovery, innovation, and the reuse of data (Wilkinson et al., 2016), while poor data management can lead to unsuccessful and harmful research projects (Kanza & Knight, 2022). RDM specialists, such as librarians, assist researchers by providing services, consulting on the data lifecycle, and offering strategies and guidelines (Bryant et al., 2023a; Redkina, 2019; Sun et al., 2023). However, defined RDM standards can create a high workload for researchers, making it difficult for them to practice RDM effectively (Wilms et al., 2020). To build effective RDM infrastructures and services, it is important to integrate the practices and perspectives of both researchers and support specialists (Sun et al., 2023). In this literature review, RDM, as presented in literature is reflected against RDM service portfolio of CSC – IT Center for Science (What CSC?, n.d.), to find out if the RDM support CSC provides, is how recommended in literature. Results of this study imply that service and support offered by CSC are according to recommendations and objectives of research data management as presented in literature. Results of the study can be used to prepare further academic studies. Results of the study have been used to support work related decision making of author of this thesis.