The constantly growing amount of digital data from various research processes and the potential to gain new insights from such research data with the aid of data science approaches make their structured management increasingly important. This is the task of the so-called research data management, which encompasses all steps necessary for the systematic preparation, organisation and provision of research data in order to preserve the scientific significance of the data.
Various approaches exist to support structured research data management, such as the development and establishment of supporting software, also known as research data management software. This approach is also the focus of the present work and is considered in particular in the context of the engineering sciences, which are typically characterised by a high degree of heterogeneity and interdisciplinarity. For this purpose, a corresponding system concept is developed and implemented, which combines novel approaches with existing technologies. The functionality and flexibility of the developed system is demonstrated and evaluated through its use within various use cases from the engineering sciences.
Despite potential challenges in the long-term and sustainable establishment of research data management software, the implemented results show the potential for use in a wide range of use cases and for possible adaptation to other research disciplines.
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M. Selzer