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BODS Interoperability Toolkit

Practical tools and workflows for validating, transforming, and using Beneficial Ownership Data Standard (BODS) data across real-world systems.

This repository brings together tools, mappings, and implementation patterns that make BODS data usable in:

  • Registry systems
  • Procurement and anti-corruption workflows
  • AML / compliance pipelines
  • Investigative and OSINT analysis
  • Graph and linked data environments

🚀 Start here

What do you want to do?

Not sure which tool fits? See the tool decision tree.


🧭 Choose your workflow

If you want to… Go here
Validate BODS data WORKFLOWS/validate-bods-data.md
Convert BODS into other formats WORKFLOWS/convert-bods-data.md
Analyse ownership networks WORKFLOWS/analyse-ownership-networks.md
Integrate BODS into systems WORKFLOWS/integrate-with-external-systems.md

🏗 Architecture overview

                                  [ BODS JSON ]
                                        │
                                        ▼
                                  [ Validation ]
                                        │
         ┌──────────────────┬───────────┴──────────┬──────────────────┐
         ▼                  ▼                      ▼                  ▼
       Neo4j         FollowTheMoney               GQL         Linked Data (RDF)
         │                  │                      │                  │
         ▼                  ▼                      ▼                  ▼
   Graph queries     Sanctions data            BigQuery        Knowledge graphs

BODS acts as an interoperability layer between beneficial ownership data and downstream systems.


👥 Who this is for

  • Registry implementers
  • Procurement / anti-corruption practitioners
  • AML / compliance engineers
  • Data journalists / investigators
  • Developers working with structured ownership data

🔧 Tools

Demos & applications

  • OpenCheckgithub.com/StephenAbbott/opencheck · live demo — LEI-anchored customer due diligence demo: fans out across national registers and open data sources, transforming corporate information into BODS v0.4 with deterministic AMLA / FATF risk signals

Core validation & interaction

Conversion & interoperability

External ecosystem tools

AI & skills


🔄 Key workflows

Validate: BODS → Validator → clean dataset

Convert:

  • Graph → Neo4j
  • Sanctions → FollowTheMoney
  • Analytics → GQL / BigQuery
  • Tabular → bodsdata
  • Linked data → RDF

Analyse:

  • Ownership chains
  • Control structures
  • Network risks

Integrate:

  • Procurement systems
  • Registries
  • AML pipelines
  • Knowledge graphs

🌐 Why this matters

Transforming BODS into graph, tabular, and linked data formats enables:

  • AI applications
  • Cross-dataset linking
  • Scalable risk detection
  • Real-world operational use

📚 Resources


🤝 Contributing

Contributions welcome:

  • Data mappings
  • Conversion tools
  • Documentation
  • Example datasets

Open an issue or pull request.

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Practical tools and workflows for validating, transforming and using Beneficial Ownership Data Standard (BODS) data across real-world systems

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