This paper demonstrates the application of a maturity model for effective data management in engineering, showing implications for research data management strategies.
With the increasing amount of data in collaborative engineering research, the need for effective and efficient data management is growing. This paper uses a maturity-based process model to examine the implementation of research data management (RDM) in engineering projects. A process model visualizes a research-supported implementation of RDM and helps researchers evaluate their data management strategies through maturity level assessment. For this approach, activities are assigned to different maturity levels based on a maturity level characteristic providing a differentiated view of the implementation of RDM. An example from an ongoing project shows the application and support of the developed maturity-based process model. The work emphasizes the importance of standardized and quality-assured data management for the success of research projects and their contribution to the scientific community
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Wawer et al. (2025) studied this question.
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