Galaxy is an excellent and well established online platform allowing researchers to operate workflows in the cloud in a FAIR and reproducible manner. Riccardo Massei, data steward in NFDI4BIOIMAGE at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, contributed a new training module to the Galaxy Training instance.
A hands-on training to use the Galaxy-OMERO suite to effectively work with Galaxy in combination with local OMERO instances is now online!

In the tutorial, researchers will learn how to use the different tools of the Galaxy OMERO-suite. The Galaxy OMERO-suite is based on the Python packages omero-py and ezomero, and it allows interactively building pipelines to upload and fetch image data in OMERO using a Galaxy workflow. Images can automatically be enriched with metadata (i.e. key-value pairs, tags, raw data, regions of interest) and uploaded to an OMERO server. The tools give the possibility to the user to intuitively fetch images from the local server and perform image analysis.

Original citation:

1. Riccardo Massei, Overview of the Galaxy OMERO-suite – Upload images and metadata in OMERO using Galaxy (Galaxy Training Materials). https://training.galaxyproject.org/training-material/topics/imaging/tutorials/omero-suite/tutorial.html Online; accessed Tue Dec 10 2024
2. Hiltemann, Saskia, Rasche, Helena et al., 2023 Galaxy Training: A Powerful Framework for Teaching! PLOS Computational Biology 10.1371/journal.pcbi.1010752
3. Batut et al., 2018 Community-Driven Data Analysis Training for Biology Cell Systems 10.1016/j.cels.2018.05.012