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Credits and Attribution

Data & Trust Alliance

This project uses the Data Provenance Standards v1.0.0 developed by the Data & Trust Alliance.

Standards Development Team

The DTA provenance standards were co-developed by 19 organizations including:

  • AARP
  • IBM
  • Mastercard
  • Deloitte
  • Nike
  • Pfizer
  • Walmart
  • CVS Health
  • Nielsen
  • Fidelity Investments
  • SAP
  • And others

The standards were developed through 150+ sessions with 50+ organizations testing and validating the framework.

Official Resources

Our Use of DTA Standards

This project: - ✅ Implements the official DTA v1.0.0 specification - ✅ Provides production-quality implementations - ✅ Adds educational examples and documentation - ✅ Compares implementation approaches (Git vs. Blockchain)

We are grateful to the Data & Trust Alliance for developing these comprehensive standards and making them publicly available.

Technology Stack

Git-Native Implementation

  • Python: Core language
  • GitPython: Git integration
  • Click: CLI framework
  • Rich: Terminal UI
  • jsonschema: Metadata validation
  • NetworkX: Lineage graph analysis
  • pytest: Testing framework

Blockchain Implementation

  • Solidity: Smart contract language
  • Hardhat: Development environment
  • ethers.js: Ethereum library
  • OpenZeppelin: Contract utilities
  • Mocha/Chai: Testing framework

Documentation

  • MkDocs: Documentation generator
  • Material for MkDocs: Theme
  • Mermaid: Diagrams
  • GitHub Pages: Hosting

Development Tools

  • Nix: Reproducible environments
  • Docker: Containerization
  • GitHub Actions: CI/CD
  • Jupyter: Interactive notebooks

Open Source Libraries

This project builds on the shoulders of giants. Special thanks to:

Python Ecosystem

  • Python Software Foundation
  • All package maintainers

Node.js Ecosystem

  • Node.js Foundation
  • npm package maintainers

Blockchain Tools

  • Ethereum Foundation
  • Hardhat team
  • OpenZeppelin team

Examples and Case Studies

The example metadata files in standards/examples/ are inspired by real-world use cases from:

  • Healthcare: DICOM standards, HIPAA guidelines
  • ML Training: HuggingFace datasets, GitHub data
  • IoT: Sensor network best practices
  • Finance: PCI-DSS compliance, GDPR requirements

All examples are synthetic/anonymized for educational purposes.

Documentation Sources

Documentation draws from:

  • DTA official specifications
  • GDPR regulatory text
  • EU AI Act proposals
  • FDA guidance on AI/ML
  • NIST data management frameworks

Contributors

This project is maintained by open-source contributors. See GitHub contributors for the full list.

How to Contribute

We welcome contributions! See our Contributing Guide for: - Code contributions - Documentation improvements - Bug reports - Feature requests - Example additions

Inspirations

This project was inspired by:

  • Data provenance research: Academic work on lineage tracking
  • Version control systems: Git's elegant design
  • Blockchain projects: Lessons from failed "blockchain for everything" projects
  • Open source movement: Commitment to transparency and collaboration

License

This project is licensed under the MIT License - see LICENSE for details.

DTA Standards License

The Data & Trust Alliance standards are used under their original terms. Please refer to the official DTA repository for their licensing terms.

Acknowledgments

Special thanks to:

  • The Data & Trust Alliance for developing open standards
  • All organizations testing and validating the DTA framework
  • Open source maintainers whose tools make this possible
  • Early users providing feedback and improvements

Disclaimer

This project is: - ✅ An educational demonstration - ✅ Production-quality code for Git-native approach - ✅ Open source and freely available

This project is NOT: - ❌ An official DTA project - ❌ Legal or compliance advice - ❌ A complete GDPR/FDA/regulatory solution - ❌ Financial or professional advice

Always consult qualified professionals for compliance and legal matters.

Contact

Citations

If you use this project in academic work, please cite:

@software{dta_provenance_demo,
  title = {DTA Provenance Standards Demo},
  author = {DTA Provenance Demo Contributors},
  year = {2024},
  url = {https://github.com/Ricoledan/dta-provenance-demo},
  note = {Production-quality implementations of Data & Trust Alliance provenance standards}
}

And cite the DTA standards:

@techreport{dta_provenance_2023,
  title = {Data Provenance Standards v1.0.0},
  author = {Data and Trust Alliance},
  year = {2023},
  institution = {Data and Trust Alliance},
  url = {https://www.dtaalliance.org/work/data-provenance-standards}
}

Thank you to everyone who made this project possible! 🙏