Speaker
Description
FAIR data management at large-scale research facilities requires more than high-level principles: it depends on practical workflows that connect planning, metadata quality, traceability, data reduction, archiving, access, and reuse. At European XFEL, myMdC is being developed as the production service through which these requirements can progressively be translated into operational data-management practice.
This work presents ongoing efforts to use myMdC to implement the facility's scientific data policy through concrete workflow components, including Data Management Plans (DMPs), metadata validation, dataset reconciliation, archival processes, and publication-oriented data handling. A key policy-driven requirement is that data reduction and archival should be completed within six months after the end of beamtime. Addressing this requirement demands earlier planning, more reliable metadata capture, stronger dataset-to-file reconciliation, and clearer workflow transitions from acquisition to downstream processing and preservation.
Recent developments therefore include richer DMP capture, improved dataset and dataset-file consistency checks, refinements to archival workflows, and extensions to metadata and permission handling needed to support policy-compliant lifecycle management. This contribution emphasises that the work is still at an early and exploratory stage: myMdC is currently being used to prototype and evaluate several possible approaches toward more advanced FAIR workflows, access models, and downstream pipelines. While the final operational model is still emerging, this work shows how policy requirements can begin to be embedded into production services to improve traceability, stewardship, and future reuse of scientific data.
