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Werner Sun (Cornell University)24/09/2026, 10:45FAIR data managementOral
The recent emergence of agentic workflows in scientific research has highlighted the urgent need for high-quality AI-ready experimental datasets for model training and validation. To be AI-ready, these datasets should be described by rich, machine-readable metadata and provenance, following FAIR data principles. Metadata and provenance perform three functions in agentic workflows: they allow...
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Fabio Dall'Antonia (Eur.XFEL (European XFEL))24/09/2026, 11:00FAIR data managementOral
European XFEL is a photon source delivering highly coherent and extremely
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short X-ray pulses at megahertz repetition rate. Drawing on lessons learned
during the first six years of operation, in particular the challenge of huge data
volumes, and on insights from participation in FAIR[1] scientific data manage-
ment initiatives, the Scientific Data Policy (SDP)[2] has been revised. In... -
Hao Hu (Institute of High Energy of Physics)24/09/2026, 11:15FAIR data managementOral
China’s High Energy Photon Source (HEPS) is the first national high-energy synchrotron radiation light source and one of the world’s brightest fourth-generation synchrotron radiation facilities. It started to operate and conduct user experiments at the end of 2025.
The 14 beamlines for the phase I of HEPS are projected to produce more than 300PB raw data annually. Efficiently storing,...
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Lei Lei (ShanghaiTech University)24/09/2026, 11:30FAIR data managementOral
The Shanghai HIgh repetitioN rate XFEL and Extreme light facility (SHINE) will support experiments such as serial crystallography, coherent diffraction imaging, and X-ray spectroscopy. These experiments will generate massive, heterogeneous and time-correlated datasets with scientific and administrative metadata. FAIR data management is therefore essential for facility operation, long-term...
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Melanie Nentwich (Deutsches Elektronen-Synchrotron DESY)24/09/2026, 11:45FAIR data managementOral
The OSCARS project represents a unique European collaboration that unites Research Infrastructures across the European Science Clusters (SCs) representing the key domains: environmental research, physics and astronomy, photon and neutron, social, and life sciences. At its core, OSCARS focuses on promoting open science and FAIR data principles and addresses this challenge by three primary...
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Spencer Bliven (PSI - Paul Scherrer Institut)24/09/2026, 12:00FAIR data managementOral
The PSI Data Catalog is Paul Scherrer Institute’s data archiving, sharing, and publishing repository. It is built around SciCat, an open source scientific metadata catalog developed by a collaboration of various international institutes and research facilities. The catalog enables research data management aligned with FAIR principles at PSI large scale facilities, including the Swiss Light...
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Allan Pinto (Brazilian Center for Research in Energy and Materials (CNPEM))24/09/2026, 12:15FAIR data managementOral
Scientific facilities are evolving toward automated and data-intensive environments in which experiments continuously generate heterogeneous and large-scale datasets that must be managed under governance requirements. Although metadata catalogues have improved data management, the transient phase between acquisition and long-term cataloguing often remains fragmented, manually handled,...
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