Tagged articles

Ontology-Driven Data Governance

7 articles · Page 1 of 1

Aug 15, 2026 · Industry Insights

Beyond 4A: Ontology-Driven Data Governance for AI-Ready Enterprise Architecture

This article explains why traditional 4A enterprise architecture fails to support AI agents, proposes an ontology semantic platform as a computable cross-domain layer, and outlines an 8-step approach to transform static architecture assets into dynamic, AI-ready business context with semantic services and action contracts.

4A architectureAI agentsData Governance

0 likes · 13 min read

Beyond 4A: Ontology-Driven Data Governance for AI-Ready Enterprise Architecture

Data Bricklaying Diary

Jul 17, 2026 · Big Data

Ontology-Driven Data Governance: Mapping Data Assets to Business Semantic Assets

This article details the third step of ontology-driven data governance: mapping existing data assets — tables, fields, documents, logs, APIs, model outputs, and human confirmations — to a business semantic model through object, attribute, state, relationship, rule, evidence, and service-action mappings, producing semantic lineage, evidence chains, and high-quality dataset candidates for semantic queries, quality validation, and agent services.

Evidence ChainOntology-Driven Data Governanceagent services

0 likes · 15 min read

Ontology-Driven Data Governance: Mapping Data Assets to Business Semantic Assets

Data Bricklaying Diary

Jul 16, 2026 · Big Data

Building Business Semantic Models for Ontology-Driven Data Governance

The article explains how to transform business models into machine-understandable business semantic models for ontology-driven data governance, covering eight key content types including concepts, relationships, states, processes, rules, metrics, evidence, and action contracts, plus transformation steps, granularity control, and deliverables such as semantic glossaries and relationship models.

AI AgentData GovernanceOntology-Driven Data Governance

0 likes · 16 min read

Building Business Semantic Models for Ontology-Driven Data Governance

Data Bricklaying Diary

Jul 15, 2026 · Big Data

Ontology-Driven Data Governance: Business Modeling from Research to Symbolic Models

This article explains how ontology-driven data governance requires thorough business research and modeling before database design, detailing a six-element framework (objects, processes, states, rules, data sources, Agent opportunities) and visual modeling techniques like OPM and BPMN to create stable semantic foundations for data mapping and AI agents.

AI agentsBPMNData Governance

0 likes · 12 min read

Ontology-Driven Data Governance: Business Modeling from Research to Symbolic Models

Data Bricklaying Diary

Jul 14, 2026 · Big Data

Ontology-Driven Data Governance: Start with Business Scenarios, Not Table Fields

This article explains why ontology-driven data governance should begin by selecting high-value business scenarios rather than analyzing existing table fields, detailing five selection criteria, a pain-point mapping method, and a value-opportunity formula with concrete examples like equipment monitoring and legal case review.

AI AgentOntology-Driven Data Governancebusiness scenario selection

0 likes · 11 min read

Ontology-Driven Data Governance: Start with Business Scenarios, Not Table Fields

Data Bricklaying Diary

Jul 13, 2026 · Big Data

Building Ontology-Driven Data Governance: Objects, Processes, Roles & Operating Mechanisms

This article presents a comprehensive framework for ontology-driven data governance that extends beyond semantic modeling into a continuous operating system covering three governance object categories, a six-step scenario-based process, eight cross-functional roles, seven operating mechanisms, and integration with existing data governance capabilities to support AI-ready semantic assets and Agent actionability.

AI data engineeringAgent systemsOntology-Driven Data Governance

0 likes · 16 min read

Building Ontology-Driven Data Governance: Objects, Processes, Roles & Operating Mechanisms

Data Bricklaying Diary

Jul 6, 2026 · Big Data

Ontology-Driven Data Governance: From Metadata to Business Semantics for AI Agents

The article argues that traditional master data and metadata management only achieve data visibility and traceability, while ontology-driven governance adds a computable business semantic layer—modeling objects, processes, states, rules, and actions via OPM and ontology—to enable AI agents to execute tasks reliably within real business contexts.

AI agentsBusiness Semantic GovernanceData Governance

0 likes · 15 min read

Ontology-Driven Data Governance: From Metadata to Business Semantics for AI Agents