Abstract
AbstractIn engineering research, various sensors and data sources are utilized for data acquisition. Together with subsequent processing and analysis, a large, heterogeneous amount of data and information is generated. To structure data and information within the research project, intelligent tools for research data management (RDM) are required. However, existing tools for RDM focus on data management during a research project and lack of capabilities to describe a technical system over this life cycle in multiple projects. Thus this paper addresses the potential of the Digital Twin (DT) concept for RDM. Based on requirements from RDM we derive specifications for a DT concept in RDM and introduce three criteria to choose suitable technical systems for DT. We present a DT for a research vehicle, implemented within the open-source Industry 4.0 DT tool “AASX Package Explorer”, to show the benefits of using a DT for RDM. KeywordsDigital TwinResearch data managementField data
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