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FAIR neuroimaging with the Neuroimaging Data Model and PyNIDM

DOI https://doi.org/10.5281/zenodo.15850765

Description

How do I produce a neuroimaging study which is FAIR: Findable, Accessible, Interoperable, and Reusable? Here we describe the Neuroimaging Data Model (NIDM), a knowledge graph-based methodology for recording all aspects of a neuroimaging study. Using an example analysis of brain size cf. age, we walk through the steps to track, organize and characterize your raw neuroimaging data, annotate derived data and share files publicly using FAIR principles.

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FAIR neuroimaging with the Neuroimaging Data Model and PyNIDM

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