The neuroscience community has witnessed a proliferation of data standards aimed at enhancing reproducibility, data sharing, and collaboration. However, this abundance creates challenges for researchers navigating which standards to adopt. This presentation provides an overview of the current ecosystem of neuroscience data standards, their interrelationships, and practical implementation guidance. We will survey established data standards for (i) storing and transmitting data, such as DICOM for neuroimaging, NWB for neurophysiological recordings, and OME-NGFF/-Zarr for microscopy images, (ii) for managing entire study datasets, such as BIDS, (iii) modality specific additional annotation of data, such as HED, and (iv) metadata model for integration and searchability in database systems, such as openMINDS and NIDM. We will also overview related tooling interface standards, such as BIDS-Apps and Boutiques. For each standard, we will outline scope, primary data domains, implementation requirements, community adoption, extension mechanisms, and integration with other standards, analysis pipelines, and platforms.This presentation aims to demystify the neuroscience standards landscape, empowering researchers to make informed choices about data management practices that enhance scientific reproducibility and collaboration. The presentation will map relationships between these standards and major data repositories, including DANDI, EMBER, NEMAR, OpenNeuro, SPARC, EBRAINS, BRAINLIFE, GIN, and others. We will highlight how these repositories and organizations like INCF promote, extend and enforce use of standards, while discussing their critical importance to ongoing initiatives such as the Brain Behavioral Quantification and Synchronization (BBQS) and BRAIN Connectivity Across Scales (BRAIN CONNECTS). We will conclude with practical decision-making guidance for researchers to help identify which standards best suit specific research needs. Case studies will demonstrate how laboratories have successfully implemented combinations of standards to enhance their research workflows and facilitate data sharing.
Rübel et al. (Tue,) studied this question.