Toolchain for Dataset Description with Contextual Recommendation from Machine-Actionable Data Management Plans

By harnessing the power of interconnected research project information, this position paper introduces a novel system designed to automate and enhance the metadata description process for research data. The system effectively leverages existing structured data from RDMO (Research Data Management Organiser), drawing insights from research projects, measurement equipment, sensors, and simulations to provide context-aware suggestions for metadata fields. We argue that this system significantly reduces the manual burden on researchers, improves the quality and consistency of metadata, and ultimately champions the FAIR principles (Findable, Accessible, Interoperable, Reusable) for all research data.