Development FAIR image analysis workflows and RDM pipelines in Galaxy

Imaging is crucial across various scientific disciplines, particularly in life sciences, where it plays a key role in studies ranging from single molecules to whole organisms. However, the complexity and sheer volume of image data present significant challenges. Managing and analyzing this data efficiently requires well-defined image processing tools and analysis pipelines that align with the FAIR principles—ensuring they are findable, accessible, interoperable, and reusable across different domains. In the frame of NFDI4BIOIMAGE1 (the National Research Data Infrastructure focusing on bioimaging in Germany), we want to find viable solutions for storing, processing, analyzing, and sharing bioimaging data. In particular, we want to develop solutions to make findable and machine-readable metadata developing analysis pipelines. In scientific research, such pipelines are crucial for maintaining data integrity, supporting reproducibility, and enabling interdisciplinary collaboration. These tools can be used by different users to retrieve images based on specific attributes as well as support quality control by identifying appropriate metadata. Galaxy, an open-source, web-based platform for data-intensive research, offers a solution by enabling the construction of reproducible pipelines for image analysis2. By integrating popular analysis software like CellProfiler and connecting with cloud services such as OMERO and IDR, Galaxy facilitates the seamless access and management of image data. This capability is particularly valuable in bioimaging, where automated pipelines can streamline the handling of complex metadata, ensuring data integrity and fostering interdisciplinary collaboration. This approach not only increases the efficiency of RDM processes in bioimaging but also contributes to the broader scientific community's efforts to embrace FAIR principles, ultimately advancing scientific discovery and innovation. In the present poster, we showed how to integrate RDM processes and tools in Galaxy. We will showcase how Images can be enriched with metadata (i.e. key-value pairs, tags, raw data, regions of interest) and uploaded to a target OME Remote Objects (OMERO) server using a novel set of OMERO tools developed with Galaxy3. Workflows give the possibility to the user to intuitively fetch images from the local server and perform image analysis (i.e. annotation). Furthermore, we will show the potential integration of eletronic lab books such as eLabFTW4, cloud storage systems (i.e. OneData)5 and interactive norebooks (Jupyter Notebooks) 6 in the Galaxy pipeline.