NeuroBagel and NiPoppy for a neuro-federation

We present an ecosystem consisting of NeuroBagel, a distributed and scalable approach based on semantic web technologies for harmonizing and sharing phenotypic and neuroimaging variables with a DataLad backend, and NiPoppy, a specification for MRI processings to integrate derived data and curation information. We used NeuroBagel tools to harmonize the OpenNeuro MRI data as well as several Parkinson datasets (Quebec Parkinson Network, Parkinson Progression Marker Initiative, etc) and will demonstrate how new neuroimaging cohorts can be defined from several distributed open or close datasets. We will show how NiPoppy, extending BIDS, could help with the standardization of the management and monitoring of neuroimaging data processing. We hope that the proposed distributed ecosystem will foster easier and more scalable neuroimaging datasharing and contribute to more diverse and large samples in machine learning applications.