🏛️ The Open Data Governance Schema (ODGS)

🧩 Why now, why this?

The Open Standard for Headless Data Governance
Decouples Business Logic from BI Tools

📉 The Problem: Definition Drift

In the modern data stack, business logic is fragmented. The definition of Gross Margin in dbt often conflicts with the DAX formula in Power BI, which differs from the calculation in Tableau.

Result: Executives don't trust the dashboard, and Data Engineers spend 40% of their time debugging "why the numbers don't match."

🚀 The Solution: Write Once, Sync Everywhere

graph TD
    subgraph PROBLEM ["❌ The Problem: Definition Drift"]
        A[CFO: 'Gross Margin' in Excel] -->|Disconnect| B[dbt: SQL Logic]
        A -->|Disconnect| C[Power BI: DAX Logic]
        B -.-|Mismatch| C
    end

    subgraph SOLUTION ["✅ The Solution: Open Governance Schema"]
        D[("JSON Schema (OGS)
        Single Source of Truth")] 
        
        D -->|Auto-Sync| E[dbt / Snowflake]
        D -->|Auto-Sync| F[Power BI / Tableau]
        D -->|Auto-Sync| G[Data Catalog / Collibra]
    end

    style D fill:#f9f,stroke:#333,stroke-width:4px,color:black
    style PROBLEM fill:#ffcccc,stroke:#333,stroke-width:1px
    style SOLUTION fill:#ccffcc,stroke:#333,stroke-width:1px

The Open Data Governance Schema (ODGS) is a vendor-neutral JSON protocol that acts as the "API" for your business definitions. By decoupling the Definition (The "What") from the Tool (The "How"), you achieve Headless Governance.

How it works

// example: standard_metrics.json
{
  "metric_id": "KPI_102",
  "name": "Gross_Margin",
  "domain": "Finance",
  "calculation_logic": {
    "abstract": "Revenue - COGS",
    "sql_standard": "SUM(gross_sales) - SUM(cost_of_goods)",
    "dax_pattern": "[Total Sales] - [Total Cost]"
  },
  "owner": "CFO_Office",
  "quality_threshold": "99.5%"
}

📂 The Protocol Structure

This repository contains the core schemas that define the "Alphabet" of Data Governance:

| File | Purpose | | :--- | :--- | | standard_metrics.json | The "Golden Record" for KPIs. Define logic, ownership, and sensitivity here. | | standard_dq_dimensions.json | The 60 industry-standard dimensions of data quality (Accuracy, Timeliness, Completeness, etc.). | | standard_data_rules.json | Technical validation rules (Regex patterns, null checks, referential integrity). | | root_cause_factors.json | A standardized taxonomy for why data breaks (e.g., Process_Gap vs Integration_Failure). | | business_process_maps.json | Maps how data entities flow through the business lifecycle. |

✅ Validation & CI/CD Integration

The repository includes a validator script that enforces the governance schema:

python3 validate_schema.py

Output:

🔍 Running Open Governance Schema Validator...
✅ Loaded 72 metrics.
✅ Loaded 50 data rules.
🎉 All Governance Checks Passed!

CI/CD Integration

Add this to your GitHub Actions workflow to enforce governance standards:

- name: Validate Governance Schema
  run: python3 validate_schema.py

This ensures that all metrics and rules have:

• Unique IDs
• Assigned owners
• Defined domains
• Clear calculation logic

📦 Installation

NPM (Node.js)

npm install odgs

Usage:

import { standardMetrics } from 'odgs';
// or
const { standardMetrics } = require('odgs');

PyPI (Python)

pip install odgs

Usage:

from odgs import standard_metrics

🛠 Usage & Implementation

Option A: Build your own Sync Engine

Fork this repository. Use these JSON files as the configuration layer in your CI/CD pipeline. Write Python/Node parsers to inject these definitions into your tools (dbt schema.yml, Power BI XMLA, etc.).

Option B: The Reference Implementation

If you prefer a managed "Headless Governance" layer that natively supports ODGS and handles the sync to Power BI/dbt automatically, feel free to see the art of possible with these end-state applications built with the same data:

• Clavis (Plain HTML, CSS, JS)
• Chartr (React v2)

These examples demonstrate the end outcome for the business user of what the Open Data Governance Schema can do.

Commercial Managed Service Partners

For commercial managed services, please visit:

• QuirkySwirl

📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Copyright © 2025 Authentic Intelligence Labs

Contributing: We welcome Pull Requests to expand the dq_dimensions or refine the root_cause_factors taxonomy.