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Introduction
Research data is generated during and as an end product of research and is usually retained by the scientific community as it is required to validate research findings (Corti et al., 2019). With advances in information and communication technologies and technical infrastructure, the generation of research data has increased significantly in both quantity and variety (Sheikh et al., 2023). Research data can take various forms, from large, well-structured data sets generated by Big Science to fragmented, smaller data sets generated by Small Science (Scaramozzino et al., 2012). Additionally, these data can be generated by different processes for different purposes. Consequently, they can occur as structured data, such as spreadsheets and tables or as semi-structured and unstructured data in formats such as JSON files, XML and HTML files, text sources, images, audio and video recordings, personal notes, emails and more (Khan et al., 2023).
These data sets serve as the basis for scientific discoveries and enable researchers to explore complex phenomena, decipher hidden patterns and drive innovation across disciplines. Against this backdrop, universities and institutions are recognising the value of research data management and institutional repositories are being established to collect, organise, store, preserve and share research data produced in an institution (Asadi et al., 2019; Francke et al., 2017). The FAIR Data Principles (Findable, Accessible, Interoperable and Reusable) provide essential guidelines for ensuring that research data is organised and made available in ways that promote data reuse and interoperability across different platforms and disciplines (Michel et al., 2016). The Digital Curation Centre’s Data Curation Lifecycle provides a structured approach to managing the lifecycle of research data, guiding institutions in curating and preserving data effectively (Higgins, 2008). While institutional repositories have traditionally focused on storing academic outputs such as publications and theses, research data has typically been managed within dedicated data repositories (Springer Nature, 2024). However, advancements in institutional repository technology and the growing demands for integration of data with publications have led an increasing number of academic institutions to plan the provision of research data services through their institutional repositories (Asadi et al., 2019). Institutional repositories comprise various components, such as data, metadata, technologies and systems, stakeholders, ownership and data ethics and administration (Joo et al.