Interdisciplinary communities, such as the life-sciences, have a strong need for efficient knowledge-transfer. In our community, computer scientists, bioimage analysts and biologists frequently come together to train each other in quantitative microscopy bioimage data analysis. For these trainings, re-usable high-quality training materials can be key. We advocate for publishing training materials according to the FAIR principles: Materials must be findable, openly accessible, stored in interoperable file formats, and most importantly made reusable by attaching open-access licenses. We are convinced that the path towards FAIR training materials leads us to more advanced and higher quality training, facilitating the advance of BioImage Analysis as a whole.
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Haase et al. (2024) studied this question.
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