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arxiv: 2606.10879 · v1 · pith:HELLZL3Bnew · submitted 2026-06-09 · 🧬 q-bio.OT

From the microscope to High Performance Computing centers, a national effort toward automated data workflows for microscopy facility users in France

classification 🧬 q-bio.OT
keywords dataimaginginfrastructuremicroscopynationalcomputingfacilitiesworkflows
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Modern biological microscopy routinely generates large and complex image datasets, including multidimensional, multimodal, and time-resolved acquisitions. While imaging technologies have rapidly evolved, data management infrastructures within microscopy facilities often remain fragmented, relying on heterogeneous local solutions that are difficult to maintain, scale, and integrate with High-Performance Computing (HPC) centers and public data repositories. To address these issues, France BioImaging (FBI), the French national infrastructure for biological imaging, has developed FBI.DATA and the associated BioImage Cloud platform. This initiative aims to provide a coordinated national infrastructure connecting microscopy facilities, centralized storage resources, HPC environments, and public bioimaging archives through interoperable and scalable workflows.The proposed architecture combines open-source technologies including OMERO for image management, iRODS for distributed data orchestration, Authentik for federated authentication, and emerging standards such as OME-Zarr and REMBI metadata recommendations. The infrastructure is designed to support the complete imaging data lifecycle, from acquisition and transfer to visualization, analysis, sharing, and long-term archiving. Beyond the technical implementation, this work presents the organizational and governance strategies required to deploy a shared national infrastructure across distributed imaging facilities. We discuss the challenges associated with interoperability, metadata standardization, sustainability, and user adoption, as well as the perspectives opened by tighter integration between imaging data and large-scale computing resources for future AI-driven bioimage analysis workflows.

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