NeuroElectroMagnetic Data Archive and Tools Resource
NEMAR goes beyond traditional data archives. Every dataset here is a living, citable research object with deep metadata integration, automated quality assessment, and infrastructure designed to make neuroscience data truly FAIR (Findable, Accessible, Interoperable, Reusable) across disciplines.
- Rich, structured metadata -- Every dataset is enriched with DataCite-compliant scholarly metadata: validated MeSH keywords, author ORCIDs, funding sources, related publications, and machine-readable descriptions
- Persistent, versioned DOIs -- Each dataset and version gets its own DOI (prefix
10.82901/NEMAR), registered with DataCite for global discoverability and citation tracking - BIDS-native -- All datasets follow the Brain Imaging Data Structure standard with automated validation on every change
- Git-based version control -- Full provenance tracking through DataLad/git-annex, with immutable data blobs on S3 and metadata history on GitHub
- Public S3 access -- No accounts, no rate limits, no paywalls for research use
Coming soon: Data quality cards, citation tracking, and integration into ML pipelines, making NEMAR a resource for researchers across neuroscience, biomedical engineering, and machine learning.
- NEMAR Portal: nemar.org/dataexplorer
- EZID/DataCite: Search NEMAR DOIs
- This org: Each
nm*repository is a dataset
npm install -g @nemarorg/nemar-cli
# Clone dataset (metadata only, lightweight)
nemar dataset clone <dataset-id>
# Download data files
nemar dataset get <dataset-id>DataLad provides efficient, selective access to large datasets stored across GitHub (metadata) and S3 (data files).
# Clone (metadata only)
datalad clone https://github.com/nemarDatasets/<dataset-id>.git
cd <dataset-id>
# Download specific files or everything
datalad get sub-01/emg/sub-01_task-wrist_emg.edf
datalad get .
# Free local copies when done
datalad drop .aws s3 ls s3://nemar/<dataset-id>/ --recursive --no-sign-request
aws s3 cp s3://nemar/<dataset-id>/path/to/file.edf . --no-sign-requestReporting issues: Open an issue on the dataset repository with the file path, expected vs actual behavior, and BIDS validator output if applicable.
Proposing changes: Fork the repository, make metadata corrections (JSON, TSV, README), and open a Pull Request. Data files are immutable; corrections are released as new versions.
Versioning: Datasets use semantic versioning. Each version gets a git tag, GitHub release, and DOI.
Each dataset specifies its own license in dataset_description.json. Always check the license before use.
- Issues: Repository-specific issue trackers
- General questions: .github discussions
- New submissions: Visit nemar.org
NEMAR -- NeuroElectroMagnetic Data Archive and Tools Resource
