Sprecher
Beschreibung
The OSCARS project brings together world-class European Research Infrastructures (RIs) in the ESFRI roadmap and beyond to foster the uptake of Open Science in Europe. OSCARS underscores the critical role of persistent identifiers (PIDs) in ensuring the findability, accessibility, interoperable, and reusability (FAIR) of research data. By assigning globally unique PIDs, OSCARS enhances long-term utility, enabling researchers to leverage data for novel applications.
Activities are centred on consolidation, composability, and engagement. Through an in-depth analysis of existing community services, OSCARS has mapped the current landscape and identified typical research workflows within the Photon and Neutron Open Science Cluster (PaNOSC). We aim to seamlessly integrate these services, fostering interoperability while introducing novel functionalities beyond their original scope; particularly in metadata enrichment and PID assignment.
A key initiative expands PID adoption for beamlines and experimental techniques. While instrument PIDs (PIDINST) are already assigned to diverse instruments, beamline PIDs remain an evolving area, particularly regarding the creation of persistent landing pages with standardised metadata. As such, we are exploring Unified Data Sheets: web-based overviews on technical details of the DESY beamline setup, which are aligned with the Ways for Light (WFL) initiative. We seek to separate the representation (webpage) from the underlying data (database) in order to streamline updates for beamline staff and user offices, ensuring consistency across multiple services, including beamline webpages, DOI services, and WFL metadata.
Additionally, OSCARS has enhanced the PaN Experimental Techniques ontology (PaNET). This ontology enables targeted applications, such as the DESY beamline finder, which helps users match beamlines to their experimental needs by querying available techniques. By integrating technique-specific metadata into datasets, PaNET can improve data discoverability while also enabling automated, technique-tailored metadata schemas during measurements.
In summary, OSCARS advances metadata interoperability and PID standardization, fostering a FAIR-aligned infrastructure that supports reproducible, collaborative, and innovative research.
| Alternative Track | 6. Harmonisation of Metadata: Closing Semantic Gaps |
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