TiM 2025: An Incubator for FAIR Image Data Management
Year: 2025
Type: conference-paper
Abstract: Biannually, German BioImaging e.V. (GerBI-GMB) organizes the GerBI-GMB Spring School "Trends in Microscopy" (TiM), an intensive microscopy training camp featuring hands-on workshops on various microscopy techniques, sample preparation, optics fundamentals, image analysis, and image data management. In 2023, TiM introduced an innovative, on-premise research data management (RDM) for image data, a concept that proved highly successful. Building on this momentum, the 2025 edition further expands its RDM initiatives. In collaboration with the DFG-funded project I3D:bio and the data steward team of the NFDI consortium NFDI4BIOIMAGE, TiM provides a unique environment for testing the complete workflow of image data management with a diverse group of users. During the meeting, an OMERO1-based framework installed on physical hardware donated for the conference facilitates FAIR data management of all acquired and processed image data. Data stewards support participants in uploading and annotating image data according to the REMBI2 metadata guidelines. Conference attendees and workshop providers are invited to contribute to a collaborative on-site test case, applying FAIR data management principles across different imaging modalities and image analysis approaches. Feedback from participants is actively gathered to refine and improve RDM strategies. We will introduce our portable data infrastructure framework and present the expanded RDM concept of TiM 2025, report on key results and statistics—including the volume of uploaded image data and its degree of FAIRness—and highlight the valuable feedback from TiM participants. https://omero-tim.gerbi-gmb.de
Authors: Boissonnet, Tom, Ahmadi, Mohsen, Hanne, Janina, Krooß, Ksenia, Moore, Josh, Schmidt, Christian, Selchow, Olaf, Wendt, Jens, Wetzker, Cornelia, Weidtkamp-Peters, Stefanie
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Deutsche Forschungsgemeinschaft
OpenAlex ID: W6930764753
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