odgs 1.2.1

The Open Data Governance Schema (ODGS) - A vendor-neutral standard for business definitions.

Open Data Governance Schema (ODGS)

"The Protocol for Algorithmic Accountability"

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What is ODGS?

ODGS is an open-source, vendor-neutral JSON protocol that serves as the single source of truth for your business logic. It solves the "Metric Drift" problem—where "Revenue" means three different things in three different tools—by defining metrics once and compiling them to Snowflake, Power BI, dbt, and AI Agents automatically.

Think of it as the "Universal Remote for Data". Instead of programming the same metric into multiple tools, you define it once in ODGS, and it syncs everywhere.

Why It Matters

• For Enterprises: Achieve EU AI Act compliance through Metric Provenance
• For Data Teams: Write definitions once, eliminate copy-paste SQL across tools
• For AI Engineers: Prevent "Semantic Hallucinations" by grounding LLMs in structured, verifiable context

Architecture

graph LR
    ODGS[("ODGS Protocol
    (JSON Truth)")] -->|Compiles to| dbt["dbt Semantic Layer"]
    ODGS -->|Compiles to| PBI["Power BI (TMSL)"]
    ODGS -->|Compiles to| Tableau["Tableau (TDS)"]
    ODGS -->|Feeds Context| AI["AI Agents (RAG)"]
    
    style ODGS fill:#4CAF50,color:white,stroke:#333,stroke-width:3px

Headless Governance means decoupling the Definition (your business rules) from the Tool (Tableau, Power BI, etc.). ODGS acts as the compilation layer that transforms abstract logic into tool-native code.

Authentic vs. Artificial Intelligence

We believe AI is only as good as the rules you give it.

• Artificial Intelligence guesses the answer based on probability
• Authentic Intelligence knows the answer based on codified human expertise

ODGS captures the Authentic Intelligence of your domain experts—the nuances, the exceptions, the business rules—and codifies them into a standard that AI can respect.

"The Table Format War is over. The Semantic War has just begun. Don't build another silo. Build on the Standard."

Quick Start

# Install
pip install odgs

# Initialize a project
odgs init my-governance-layer
cd my-governance-layer

# Validate your schemas
odgs validate

# Build artifacts for all downstream tools
odgs build --target all

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Documentation

📘 Complete Guide
End-to-end journey from concept to implementation. Includes quickstart, schema reference, CLI commands, and adapter examples.

🎯 Strategic Vision
The business case for ODGS: Market opportunity, AI Safety compliance, academic partnerships, and the "Swiss Army Knife" thesis.

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The 7 Core Schemas

Schema	Purpose
standard_metrics.json	KPI definitions (logic, ownership, compliance tags)
standard_data_rules.json	Validation rules (regex, nulls, ranges)
standard_dq_dimensions.json	Data quality categories (Accuracy, Timeliness)
root_cause_factors.json	Taxonomy for data failures (Process Gap, Integration Failure)
business_process_maps.json	Process workflows (Order-to-Cash, Procure-to-Pay)
physical_data_map.json	Mapping logic to database tables/columns
ontology_graph.json	Knowledge graph (Customer has Orders)

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Contributing

We welcome contributions! Whether you're:

• Researchers: Expanding the DQ Dimensions taxonomy
• Engineers: Building adapters for new tools (Looker, Qlik)
• Domain Experts: Refining the Root Cause taxonomy

Please see CONTRIBUTING.md for guidelines.

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License

Apache License 2.0 - see LICENSE for details.

Copyright © 2025 Authentic Intelligence Labs