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Governance Assets

Business vocabulary and classification systems for data governance

Governance assets in OpenMetadata provide the foundation for organizing, standardizing, and controlling business terminology and data classifications. The governance framework consists of two parallel hierarchies: Glossaries for business vocabulary and Classifications for data tagging.

Hierarchy Overview

OpenMetadata governance uses two complementary hierarchies:

Glossary Hierarchy

graph TD
    A[Glossary] --> B1[GlossaryTerm 1]
    A --> B2[GlossaryTerm 2]
    B1 --> C1[Child Term 1.1]
    B1 --> C2[Child Term 1.2]
    B2 --> C3[Child Term 2.1]
    C1 --> D1[Child Term 1.1.1]

    style A fill:#667eea,color:#fff
    style B1 fill:#764ba2,color:#fff
    style B2 fill:#764ba2,color:#fff
    style C1 fill:#f093fb,color:#fff
    style C2 fill:#f093fb,color:#fff
    style C3 fill:#f093fb,color:#fff
    style D1 fill:#fa709a,color:#fff

Classification Hierarchy

graph TD
    A[Classification] --> B1[Tag 1]
    A --> B2[Tag 2]
    B1 --> C1[Tag 1.1]
    B1 --> C2[Tag 1.2]
    B2 --> C3[Tag 2.1]
    C1 --> D1[Tag 1.1.1]

    style A fill:#0061f2,color:#fff
    style B1 fill:#6900c7,color:#fff
    style B2 fill:#6900c7,color:#fff
    style C1 fill:#00ac69,color:#fff
    style C2 fill:#00ac69,color:#fff
    style C3 fill:#00ac69,color:#fff
    style D1 fill:#4facfe,color:#fff

Why This Hierarchy?

Glossary

Purpose: Container for organizing business terms and definitions

A Glossary is a collection of business terms that define concepts, processes, and entities used across your organization. Glossaries provide a controlled vocabulary that ensures everyone speaks the same language when discussing data.

Examples:

  • BusinessGlossary - Core business terminology
  • FinanceGlossary - Financial terms and metrics
  • MarketingGlossary - Marketing campaign and segment definitions
  • RegulatoryGlossary - Compliance and legal terminology

Why needed: Organizations often have thousands of data assets but lack a common understanding of business concepts. Different teams may use different names for the same concept (e.g., "customer" vs. "client" vs. "account"). Glossaries establish the single source of truth for business definitions.

Key Features:

  • Reviewers: Designated users who approve term changes
  • Mutually Exclusive Terms: Option to enforce that only one term can apply
  • Domain Assignment: Link glossary to business domains
  • Ownership: Team or user responsible for maintaining the glossary

View Glossary Specification →

GlossaryTerm

Purpose: Individual business concept with definition and relationships

A GlossaryTerm represents a single business concept with its formal definition, synonyms, related terms, and references. Terms can have parent-child relationships to create hierarchical taxonomies.

Examples:

  • Customer - "An individual or organization that purchases products or services"
  • MonthlyRecurringRevenue - "Revenue that recurs every month from subscriptions"
  • ChurnRate - "Percentage of customers who cancel in a given period"

Why needed: Terms provide the atomic unit of business vocabulary. Each term documents: - Formal Definition: What the term means - Synonyms: Alternative names used in different contexts - Related Terms: Connections to other business concepts - Asset Links: Tables, columns, or dashboards using this term - References: Documentation or standards that define the term

Hierarchical Structure: Terms can be nested to create taxonomies: 

CustomerSegment (parent)
├── EnterpriseCustomer (child)
├── SMBCustomer (child)
└── IndividualCustomer (child)

View GlossaryTerm Specification →

Classification

Purpose: System for organizing and applying tags to data assets

A Classification is a category system that contains tags for labeling data assets. Classifications enable governance policies like access control, data quality rules, and retention policies based on data characteristics.

Examples:

  • PII - Personal Identifiable Information classification
  • DataQuality - Quality assessment tags
  • Tier - Data importance levels
  • Sensitivity - Data sensitivity classifications

Why needed: Tags enable: - Access Control: Restrict access based on sensitivity tags - Compliance: Mark data requiring special handling (GDPR, HIPAA, etc.) - Quality Management: Track data quality levels - Lifecycle Management: Define retention and archival policies

Mutually Exclusive: Classifications can enforce that only one tag from the set can be applied (e.g., Tier 1, Tier 2, or Tier 3 - not multiple).

View Classification Specification →

Tag

Purpose: Individual label that can be applied to data assets

A Tag is a label within a Classification that can be attached to tables, columns, dashboards, and other data assets. Tags flow through lineage, enabling automatic propagation of governance metadata.

Examples:

  • PII.Sensitive - Contains sensitive personal information
  • PII.NonSensitive - Contains non-sensitive personal information
  • Tier.Tier1 - Critical business data
  • Tier.Tier2 - Important business data

Why needed: Tags provide the mechanism to: - Label Data: Mark assets with governance metadata - Enforce Policies: Apply rules based on tags (e.g., mask PII columns) - Track Lineage: See how sensitive data flows through pipelines - Enable Discovery: Filter and find assets by governance attributes

Hierarchical Structure: Tags can be nested within classifications: 

PII (classification)
├── Sensitive (tag)
│   ├── Email (tag)
│   └── SSN (tag)
└── NonSensitive (tag)
    ├── Name (tag)
    └── ZipCode (tag)

View Tag Specification →

Common Patterns

Pattern 1: Business Glossary Structure

Business Glossary → Customer (term)
                 → Revenue (term) → AnnualRecurringRevenue (child term)
                                  → MonthlyRecurringRevenue (child term)
                 → Churn (term)

Organize business concepts hierarchically with parent-child relationships.

Pattern 2: Data Classification System

PII Classification → Sensitive (tag) → Email (tag)
                                    → SSN (tag)
                  → NonSensitive (tag) → Name (tag)
                                      → ZipCode (tag)

Create nested tag hierarchies for fine-grained governance.

Pattern 3: Domain-Specific Glossaries

Finance Glossary → EBITDA (term)
                 → CashFlow (term)

Marketing Glossary → ConversionRate (term)
                   → CustomerLifetimeValue (term)

Engineering Glossary → Uptime (term)
                     → Latency (term)

Multiple glossaries for different business domains or teams.

Real-World Example

Here's how an e-commerce company implements governance:

graph TB
    subgraph Glossaries
        G1[Business Glossary]
        G2[Marketing Glossary]

        G1 --> T1[Customer]
        G1 --> T2[Order]
        G1 --> T3[Revenue]

        G2 --> T4[Campaign]
        G2 --> T5[Conversion Rate]
    end

    subgraph Classifications
        C1[PII Classification]
        C2[Tier Classification]

        C1 --> TAG1[Sensitive]
        C1 --> TAG2[NonSensitive]

        C2 --> TAG3[Tier1]
        C2 --> TAG4[Tier2]
    end

    subgraph "Data Assets"
        TABLE1[customers table]
        COL1[email column]
        COL2[name column]
    end

    T1 -.->|defines| TABLE1
    TAG1 -.->|applied to| COL1
    TAG2 -.->|applied to| COL2
    TAG3 -.->|applied to| TABLE1

    style G1 fill:#667eea,color:#fff
    style G2 fill:#667eea,color:#fff
    style C1 fill:#0061f2,color:#fff
    style C2 fill:#0061f2,color:#fff
    style T1 fill:#764ba2,color:#fff
    style T2 fill:#764ba2,color:#fff
    style T3 fill:#764ba2,color:#fff
    style T4 fill:#764ba2,color:#fff
    style T5 fill:#764ba2,color:#fff
    style TAG1 fill:#6900c7,color:#fff
    style TAG2 fill:#6900c7,color:#fff
    style TAG3 fill:#00ac69,color:#fff
    style TAG4 fill:#00ac69,color:#fff
    style TABLE1 fill:#4facfe,color:#fff
    style COL1 fill:#00f2fe,color:#fff
    style COL2 fill:#00f2fe,color:#fff

Governance Implementation:

  1. Business Glossary:
  2. Defines key business concepts like "Customer", "Order", "Revenue"
  3. Marketing team maintains separate glossary for campaign terminology

  4. Terms link to actual data assets (tables, dashboards)

  5. PII Classification:

  6. "Sensitive" tags applied to email, SSN, phone numbers
  7. "NonSensitive" tags applied to names, zip codes

  8. Enables automated masking and access control policies

  9. Tier Classification:

  10. "Tier1" marks critical business data requiring high availability
  11. "Tier2" marks important data with standard SLAs

  12. Drives backup, replication, and monitoring policies

  13. Integration:

  14. Glossary terms define what data means
  15. Classification tags control how data is handled
  16. Both flow through lineage automatically

Glossary vs Classification

Understanding when to use each:

Aspect Glossary Classification
Purpose Define business concepts Categorize and label data
Content Definitions, synonyms, relationships Tags for governance policies
Applied To Can be associated with assets Directly tagged to assets
Hierarchy Parent-child terms Parent-child tags
Use Case Business understanding Policy enforcement
Example "What is a Customer?" "This column contains PII"
Mutability Definitions evolve slowly Tags change as data evolves
Ownership Business analysts, domain experts Data governance team

Best Practice: Use glossaries to establish shared business vocabulary and classifications to implement governance policies.

Comprehensive Governance Example

A financial services company's complete governance structure:

graph TB
    subgraph "Business Context (Glossaries)"
        BG[Business Glossary]
        FG[Finance Glossary]
        CG[Compliance Glossary]

        BG --> BT1[Customer]
        BG --> BT2[Account]

        FG --> FT1[Asset Under Management]
        FG --> FT2[Net Asset Value]

        CG --> CT1[KYC]
        CG --> CT2[AML Check]

        BT1 --> BT1A[Retail Customer]
        BT1 --> BT1B[Institutional Customer]
    end

    subgraph "Data Control (Classifications)"
        PC[PII Classification]
        DC[Data Tier Classification]
        RC[Regulatory Classification]

        PC --> PT1[Sensitive PII]
        PC --> PT2[Standard PII]

        DC --> DT1[Tier 1 - Critical]
        DC --> DT2[Tier 2 - Important]
        DC --> DT3[Tier 3 - Standard]

        RC --> RT1[GDPR]
        RC --> RT2[SOX]
        RC --> RT3[FINRA]
    end

    subgraph "Data Assets"
        T1[customer_profiles table]
        T2[transactions table]
        T3[account_balances table]

        C1[ssn column]
        C2[email column]
        C3[name column]
    end

    BT1 -.->|defines| T1
    FT2 -.->|defines| T3

    PT1 -.->|applied to| C1
    PT2 -.->|applied to| C2
    DT1 -.->|applied to| T1
    DT1 -.->|applied to| T3
    RT1 -.->|applied to| T1
    RT2 -.->|applied to| T3

    style BG fill:#667eea,color:#fff
    style FG fill:#667eea,color:#fff
    style CG fill:#667eea,color:#fff
    style PC fill:#0061f2,color:#fff
    style DC fill:#0061f2,color:#fff
    style RC fill:#0061f2,color:#fff
    style T1 fill:#4facfe,color:#fff
    style T2 fill:#4facfe,color:#fff
    style T3 fill:#4facfe,color:#fff

Implementation:

  1. Glossaries establish shared vocabulary across teams
  2. Classifications enforce governance policies
  3. Tags flow through lineage automatically
  4. Policies trigger based on tags (access control, masking, retention)
  5. Ownership assigned at glossary and classification levels

Benefits:

  • Automated policy enforcement based on tags
  • Consistent business definitions across the organization
  • Regulatory compliance through classification tracking
  • Impact analysis through term-to-asset relationships

Entity Specifications

Each entity in the governance framework has complete specifications:

Entity Description Specification
Glossary Business vocabulary container View Spec
GlossaryTerm Individual business concept View Spec
Classification Tag category system View Spec
Tag Individual data label View Spec

Each specification includes: - Complete field reference - JSON Schema definition - RDF/OWL ontology representation - JSON-LD context and examples - Real-world use cases - API operations

Governance Best Practices

1. Start with Core Glossaries

Begin with a single business glossary containing 20-30 essential terms. Expand gradually as teams adopt the framework.

2. Align Classifications with Policies

Create classifications that map directly to governance policies (PII for masking, Tier for SLAs, Retention for archival).

3. Establish Ownership

Assign reviewers to glossaries and owners to classifications. Clear ownership ensures quality and consistency.

Connect glossary terms to actual tables and columns. This bridges business and technical metadata.

5. Automate Tag Propagation

Use lineage to propagate tags automatically. When a source column has a PII tag, derived columns inherit it.

6. Review Regularly

Schedule quarterly reviews of glossaries and classifications to ensure they remain current and relevant.

Next Steps

  1. Explore entities - Click through each specification above
  2. See examples - Check out governance examples
  3. Understand lineage - Learn how tags flow through lineage
  4. Implementation guide - Review getting started with governance