Open data infrastructures are rapidly reshaping the landscape of neuroscience by enabling greater reproducibility through transparency, reusability, and collaboration, thus providing a foundation for sustainable and scalable scientific progress. This paper presents a systematic audit of the Neuroelectromagnetic Data Archive and Repository (NEMAR), a platform supporting the sharing and reuse of EEG, MEG, and iEEG datasets standardized through the Brain Imaging Data Structure (BIDS) format. Drawing on a detailed analysis of over 300 publicly available datasets, we assess the composition, metadata quality, and population coverage of data in NEMAR. Our findings reveal significant momentum in data sharing practices, particularly in EEG, and highlight key challenges, including inconsistent metadata, underrepresentation of clinical populations, and variable adherence to data standards. These insights highlight the importance of targeted support for policy and cultural development to ensure open repositories like NEMAR are not only accessible but also equitable, reusable, and scientifically robust.
Brandmeyer et al. (2026) studied this question.