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Tagged articles

ontology modeling

11 articles · Page 1 of 1
Digital Deification
Digital Deification
Oct 14, 2026 · R&D Management

FDE Four-Ring Methodology: Delivering AI Value Through Four Integrated Rings

The article details the FDE four-ring methodology—business reshaping, AI engineering, evaluation & verification, and production operations—emphasizing they form an integrated network, not sequential stages, with ontology modeling as the semantic foundation, and highlights pitfalls, deliverables, and the need for co-creation and agile iteration.

AI deliveryAI engineeringFDE
0 likes · 16 min read
FDE Four-Ring Methodology: Delivering AI Value Through Four Integrated Rings
Data Bricklaying Diary
Data Bricklaying Diary
Oct 13, 2026 · Industry Insights

Don't Wait for Perfect Data: Phased Gates for Ontology Pilots

The article argues against waiting for full data governance before starting ontology pilots, proposing a four-phase gated approach—concept verification, sample verification, continuous query, and business execution—with explicit three-state data quality handling (satisfied, unsatisfied, unknown) and clear separation of query conclusions from execution permissions, using a warehouse shortage assistant case study.

TOCTOUW3C DQVdata governance
0 likes · 16 min read
Don't Wait for Perfect Data: Phased Gates for Ontology Pilots
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Sep 11, 2026 · Industry Insights

Why Material Issuance ≠ Cost Transfer: OntoL's Ontology Modeling Fixes Business-Finance Disconnect

OntoL uses dual ontology modeling — separating business material flow from financial cost recognition — to decouple warehouse issuance from profit-and-loss impact, enabling automatic WIP tracking, real-time discrepancy detection, and full audit traceability, cutting month-end closing from seven days to half a day in manufacturing case studies.

TBox/ABoxWIP cost accountingaudit traceability
0 likes · 13 min read
Why Material Issuance ≠ Cost Transfer: OntoL's Ontology Modeling Fixes Business-Finance Disconnect
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Sep 11, 2026 · Backend Development

Why 90% of ERP Implementations Fail: The Hidden Semantic Gap OntoL Ontology Fixes

This article explains why ERP systems with identical workflows produce vastly different outcomes, revealing that business semantics and rules—not processes—determine success, and demonstrates how OntoL's ontology modeling with TBox/ABox layers and inference engines standardizes constraints, versioning, and traceability across manufacturing scenarios.

BOMECNERP
0 likes · 25 min read
Why 90% of ERP Implementations Fail: The Hidden Semantic Gap OntoL Ontology Fixes
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Sep 7, 2026 · Industry Insights

Palantir's 8 Commercial Case Studies: Ontology Modeling Saves Millions Without Replacing Legacy Systems

This article analyzes eight Palantir Foundry deployments across aerospace, consumer goods, energy, and insurance, showing how ontology-based data integration enables real-time decision-making, cuts costs by millions, and accelerates digital transformation without replacing existing ERP or MES systems.

Case StudiesDecision IntelligenceFoundry
0 likes · 12 min read
Palantir's 8 Commercial Case Studies: Ontology Modeling Saves Millions Without Replacing Legacy Systems
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Sep 3, 2026 · Industry Insights

OntoL: Ontology Modeling & Semantic Layer for Enterprise Knowledge Governance

This article analyzes OntoL, an ontology modeling tool for enterprise knowledge governance, detailing its three-layer architecture, core capabilities like visual modeling and versioning, applicable scenarios, current technical limitations, and future roadmap including SHACL constraints and federated query.

Knowledge GovernanceKnowledge GraphOWL
0 likes · 9 min read
OntoL: Ontology Modeling & Semantic Layer for Enterprise Knowledge Governance
Digital Deification
Digital Deification
Sep 1, 2026 · Industry Insights

GB/T 48000.3: Three Shifts for Enterprise Knowledge Modeling from Documents to Actionable Ontologies

The article interprets China's GB/T 48000.3 ontology modeling standard, highlighting its core principle of separating knowledge content from representation, and derives three enterprise digitalization shifts: moving from document chunks to business information units, from retrieval to constraint validation, and from answer generation to action-driven knowledge modeling.

GB/T 48000.3action-driven AIbusiness semantics
0 likes · 7 min read
GB/T 48000.3: Three Shifts for Enterprise Knowledge Modeling from Documents to Actionable Ontologies
Data Bricklaying Diary
Data Bricklaying Diary
Sep 1, 2026 · Fundamentals

Beyond Consistency Checks: A 7-Layer Acceptance Framework for Ontology Models

This article presents a seven-layer acceptance framework for ontology models that moves beyond consistency reasoning and expert review, covering capability questions, semantic constraints, real data mapping, rule execution with unknown states, exception handling and action contracts, version traceability, and controlled business outcomes with multi-role sign-off.

business-outcomesconsistency-reasoningexpert review
0 likes · 26 min read
Beyond Consistency Checks: A 7-Layer Acceptance Framework for Ontology Models
Data Bricklaying Diary
Data Bricklaying Diary
Aug 24, 2026 · Fundamentals

Ontology Isn't Esoteric: You Already Process Its Raw Materials Daily

This article explains that ontology modeling uses familiar business objects, attributes, relationships, and constraints from daily data and process work, but adds cross-system unified semantics, explicit computable constraints, machine verification, and continuous operations to enable data, rules, systems, and AI agents to collaborate on a shared business world.

AI readinessEnterprise ArchitectureOWL
0 likes · 20 min read
Ontology Isn't Esoteric: You Already Process Its Raw Materials Daily
Data Bricklaying Diary
Data Bricklaying Diary
Aug 22, 2026 · R&D Management

From Vague Requirements to Verifiable Business Scenarios: A 7-Step Ontology Research Method

This article outlines a seven-step business research methodology for ontology modeling, transforming vague requirements into clear, verifiable business scenarios by distinguishing facts, rules, judgments, and hypotheses, evaluating candidate opportunities, defining value narratives and boundaries, and producing a scenario definition card as a modeling input.

business researchdata governanceknowledge engineering
0 likes · 29 min read
From Vague Requirements to Verifiable Business Scenarios: A 7-Step Ontology Research Method
DataFunSummit
DataFunSummit
May 2, 2026 · Artificial Intelligence

How Palantir’s 4‑Layer Ontology Architecture Enables Buildings, Tenants, and Data to ‘Talk’

Healthpeak transformed its commercial‑real‑estate operations by replacing fragmented spreadsheets with Palantir’s AI Platform (AIP), using a four‑layer architecture and ontology‑driven modeling to automate billing, detect anomalies, and orchestrate workflows, dramatically cutting manual effort, errors, and scaling costs.

AI workflow automationCommercial Real EstatePalantir
0 likes · 18 min read
How Palantir’s 4‑Layer Ontology Architecture Enables Buildings, Tenants, and Data to ‘Talk’