Research datasets in Brain Imaging Data Structure (BIDS) format, hosted on GitHub + AWS S3 infrastructure.

This organization hosts BIDS-formatted datasets that cannot be hosted on public repositories (OpenNeuro, Zenodo, etc.) due to restrictive licenses, while remaining freely available for research use.

Hosting criteria:

• ✅ BIDS-compliant format
• ✅ Freely available for academic/research use
• ✅ Restrictive license preventing hosting on public repositories (e.g., non-commercial, research-only)

DataLad enables efficient access to large datasets stored across GitHub (metadata) and S3 (data files).

# Install DataLad (macOS)
brew install datalad

# Clone dataset (lightweight - only downloads metadata)
datalad clone https://github.com/nemarDatasets/nm000107.git
cd nm000107

# Download specific files
datalad get sub-01/emg/sub-01_task-wrist_emg.edf

# Download all data
datalad get .

# Remove data files (keep metadata)
datalad drop .

# Clone repository (metadata only, no large files)
git clone https://github.com/nemarDatasets/nm000107.git
cd nm000107

# View S3 URLs for data files
cat .git/annex/objects/.../...

Large binary files (.edf, .bdf) are stored on S3 with public read access:

# List dataset files
aws s3 ls s3://nemar/nm000107/ --recursive --no-sign-request

# Download specific file
aws s3 cp s3://nemar/nm000107/path/to/file.edf . --no-sign-request

Found incorrect metadata, missing files, or BIDS compliance issues?

1. Go to the dataset repository (e.g., nm000107)
2. Click Issues → New Issue
3. Describe the problem with:
   • File path or subject ID
   • Expected vs actual behavior
   • BIDS validator output (if applicable)

For metadata corrections (JSON, TSV, README):

1. Fork the dataset repository
2. Clone your fork locally
3. Make changes to metadata files
4. Commit with clear message: fix: correct participant age in participants.tsv
5. Push to your fork
6. Open Pull Request with description of changes

For data file issues:

• File Issues only (data files are immutable annexes)
• Corrections will be released as new dataset versions

Datasets use semantic versioning (v1.0.0, v1.1.0, etc.):

• Patch (v1.0.1): Metadata fixes, documentation updates
• Minor (v1.1.0): New participants, additional sessions
• Major (v2.0.0): Breaking changes, restructuring

Each version gets:

• Git tag
• GitHub release
• Zenodo DOI (versioned)

If you're a dataset maintainer and need to create a new version:

Step 1: Update Metadata

# Clone dataset
datalad clone https://github.com/nemarDatasets/nm000XXX.git
cd nm000XXX

# Update dataset_description.json, README.md, or other metadata
# Make sure Authors field lists only data creators (not curators)

# Save changes
datalad save -m "fix: update metadata with complete author information"

# Push and create PR
datalad push --to origin
gh pr create --title "Update dataset metadata"

Step 2: Version Bump (after PR merged)

Minor version updates (v1.0.0 → v1.1.0):

• Metadata improvements
• Adding participants/sessions
• Non-breaking changes

This creates:

• New git tag
• New GitHub release
• New version DOI under same concept DOI

Important Notes:

• ✅ Only modify metadata files (*.json, *.tsv, *.md)
• ❌ Never modify data files (*.edf, *.bdf) - create new dataset instead
• ✅ Remove curator names from Authors field
• ✅ List only original data creators in Authors
• ⚠️ DOIs are permanent - review carefully before publication

For detailed workflow, see repository documentation.

Each dataset has its own license specified in dataset_description.json and root LICENSE file. Common restrictions:

• ✅ Academic/research use
• ❌ Commercial use
• ❌ Redistribution without attribution
• ❌ Public repository hosting (e.g., OpenNeuro)

Always check the dataset's LICENSE file before use.

Infrastructure:

• GitHub: Metadata (JSON, TSV, README) + DataLad/git-annex pointers
• AWS S3: Binary data files (EMG recordings)
• Zenodo: DOI registration + archived releases

BIDS Validation:

• Datasets pass basic BIDS checks (required files, structure)
• Full validator compliance is work in progress

Data Access:

• S3 public read access (no AWS account needed)
• No rate limiting on downloads
• Free egress for research use

• Issues: Use repository-specific issue trackers
• General questions: Open discussion in .github repository
• New dataset submissions: Contact dataset maintainers

Hosted by NEMAR (NeuroElectroMagnetic Archive) infrastructure