Commentary Thread
type: Class
comment: A thematic thread within the discussion, potentially spanning multiple comments.

a9
type: Answer
text: Veronika Heimsbakk: Getting ontology from tables into code is straightforward — 'four lines of Python' using tools like maplib and OTTR templates to map structured data to ontology properties.

Set Up Compilation
type: HowToStep
description: Implement a build step that validates logical consistency — contradictions or unexpected entailments should break the build. Jacob Friedman notes OWL is based on Description Logic: leverage its formal semantics for normalization checks.
is part of: Adopting Ontology as Code
position: 3

commentAslamAhamed
type: Comment
author: Aslam Ahamed
is part of: Comments and Discussion
text: Comment text not captured in LinkedIn guest view.

Michael Graham
type: Person
description: Commenter on Tony Seale's ontology-as-code post.

commentRobertSanderson
type: Comment
author: Robert Sanderson
is part of: Comments and Discussion
text: Linked Art's compile pipeline processes RDFS+OWL into a Python class library. Engineers write familiar code like 'r = Person(id="Rob"); r.name = "Rob"' instead of raw triple adds. Ontology is code — and transpiles to other code that makes it more developer friendly.

featured insight
type: Property
comment: Designates an insight as the anchor/featured commentary for the analysis.

Edward Henry
type: Person
description: AI practitioner warning against addressing upstream problems downstream — ontology-as-code formalizes meaning at the source.

a5
type: Answer
text: Honorio J. Padrón III distinguishes operational ontologies (what exists) from decision ontologies (who owns each decision, what triggers it, what action it generates). An operational ontology makes data legible; a decision ontology makes the enterprise executable. The decision ontology is 'source code for your will to act.' His CLEARED platform operationalizes this distinction.

How do you bridge tables to ontology code?
type: Question
accepted answer: a9
text: How do you bridge existing tables to ontology code?

commentKyleTobin
type: Comment
author: Kyle Tobin
is part of: Comments and Discussion
text: Do your ontology in Pydantic so entities are executable — they don't just describe their own behavior. They conduct it too! Ontology should be reflected in application architecture, not smeared across four duplicative components.

Veronika Heimsbakk
type: Person
description: Knowledge Graph Specialist, author of 'SHACL for the Practitioner' and advocate for the Semantic Medallion architecture.

commentStepan
type: Comment
author: Stepan Karandin
is part of: Comments and Discussion
text: Ontology is information. Databases or code are just data formats. The relational model is the worst kind of normalization for ontology. Mathematically, ontology could be described as a graph.

Harish Iyer
type: Person
description: Product-strategy thinker focused on the ontology guardian role at the intersection of engineering, design, and product.

Semantic Web Stack
type: Concept
type: DefinedTerm
description: The W3C technology stack including RDF, SPARQL, OWL, and JSON-LD — now gelling naturally with LLMs for a filesystem-based ontology workflow.
definition: W3C technology stack for linked data.
in scheme: Ontology as Code Glossary

Live in Plain Text
type: Ontology Pillar
type: DefinedTerm
description: Ontologies should live in plain text — enabling diffs, branches, blame, and pull requests. You want LLMs to read, navigate and edit the source directly, exactly the way it works with a codebase.

a3
type: Answer
text: Plain text enables diffs, branches, blame, and pull requests — standard software engineering tooling. It also allows LLMs to read, navigate, and edit the source directly, exactly like working with a codebase.

Ontology Pillar
type: Class
comment: A foundational principle of the ontology-as-code approach.

The Knowledge Graph Guys
type: CreativeWork
description: Tony Seale's newsletter on knowledge graphs and ontology engineering.

Mark O'Donovan
type: Person
description: Data practitioner on a personal journey from spreadsheet to graph database.

Ontology as Code
type: DefinedTerm
description: The practice of treating ontologies as source code rather than database artifacts — with compilation, version control, and engineering governance.

rdf-infographic-skill v2
type: SoftwareApplication
description: Generated the companion HTML infographic and Markdown document (Edition 2).

commentMarkODonovan
type: Comment
author: Mark O'Donovan
is part of: Comments and Discussion
text: Started as an idea in my head, then a note in a notebook, then an Excel table, then a SQL table — now looking at GraphDB. A personal journey toward ontology maturity.

Linked Art
type: DefinedTerm
description: A linked data profile for cultural heritage that compiles RDFS+OWL ontologies into Python class libraries — demonstrating ontology-as-code in production.

Industry
type: Class

a6
type: Answer
text: A term coined by Tony Seale for commoditized, fast-food approaches to ontology — treating ontologies as mass-produced rather than carefully engineered artifacts. It is the antithesis of the ontology-as-code philosophy.

Governance
type: Concept
type: DefinedTerm
description: Engineering discipline applied to ontology management — version control, code review, CI/CD pipelines for meaning.
definition: Engineering discipline for ontology management.
in scheme: Ontology as Code Glossary

commentMarkPippins
type: Comment
author: Mark Pippins
is part of: Comments and Discussion
text: Comment text not captured in LinkedIn guest view.

Kingsley Uyi Idehen
type: Person
description: Founder and CEO of OpenLink Software, creator of Virtuoso, Semantic Web and Linked Data pioneer. Advocate for the Semantic Medallion architecture and LLM-mediated knowledge graph construction.

a7
type: Answer
text: RDF-Turtle is human-readable shorthand for triples. JSON-LD has more tooling support. Combined with LLMs, the stack now provides both readability and tooling — bridging the historical gap that made ontology management difficult. As Kingsley Idehen notes, files in a DAV folder bound to Virtuoso automatically become part of a live quad store.

Extract Your Ontology from Database Tables
type: HowToStep
description: Use four lines of Python (maplib + OTTR templates) to map existing table-based ontology rows into RDF triples in a plain-text file. As Veronika Heimsbakk demonstrates: the extraction is straightforward.
is part of: Adopting Ontology as Code
position: 1

Thomas Smith
type: Person
description: Database theorist: relational DBs index binary trees (2D), triples define 3D graphs, SQL chokes on circular references.

Gabor Csepregi
type: Person
description: Knowledge graph practitioner who appreciates clear ontology explanation.

Adopting Ontology as Code
type: HowTo
description: Seven steps to transition from database-centric to code-centric ontology management, incorporating insights from all 14 discussion participants.
has part: Extract Your Ontology from Database Tables
has part: Store in Plain Text (Turtle or JSON-LD)
has part: Set Up Compilation
has part: Version Control with Git
has part: Enable LLM-Mediated Editing
has part: Bind to a Backend RDF DBMS
has part: Define Decision Ownership and Make It Executable
is part of: Your ontology is source code for your meaning.
step: Extract Your Ontology from Database Tables
step: Store in Plain Text (Turtle or JSON-LD)
step: Set Up Compilation
step: Version Control with Git
step: Enable LLM-Mediated Editing
step: Bind to a Backend RDF DBMS
step: Define Decision Ownership and Make It Executable

commentHarish
type: Comment
author: Harish Iyer
is part of: Comments and Discussion
text: The gap between engineering, design and product is narrowing. Ontology should no longer be a layer but the language of the company. Context switching will be replaced by context expansion. Who owns the ontology guardian role?

commentEdwardHenry
type: Comment
author: Edward Henry
is part of: Comments and Discussion
text: The biggest illusion in AI is the gap. We are trying to address upstream problems downstream, trying to turn LLM slop into something real with great ideas like ontology-as-code.

commentGaborCsepregi
type: Comment
author: Gabor Csepregi
is part of: Comments and Discussion
text: Can't remember the last time I had ontology and knowledge graph related content properly explained.

Pydantic-Executable Ontology
type: Concept
type: DefinedTerm
description: Kyle Tobin's approach: ontologies defined in Pydantic where entities are executable — they don't just describe behavior, they conduct it. Ontology reflected in application architecture.
definition: Executable ontology in Pydantic.
in scheme: Ontology as Code Glossary

The Three Pillars of Ontology as Code
type: ArticleSection
description: Tony Seale's three foundational principles for treating ontologies as source code.
has part: Compile — Not Just Parse
has part: Live in Plain Text
has part: Governed Like Code
is part of: Your ontology is source code for your meaning.

Featured Insight: LLMs + Semantic Web — A Natural Ecosystem
type: ArticleSection
description: Kingsley Idehen's anchor commentary on how LLMs and the Semantic Web stack form a natural ecosystem for ontology management.
has part: kingsleyInsight
is part of: Your ontology is source code for your meaning.

RDF-Turtle
type: Concept
type: DefinedTerm
description: Human-readable shorthand notation for RDF triples — preferred for LLM-mediated ontology creation and filesystem-based management.
definition: Human-readable RDF notation.
in scheme: Ontology as Code Glossary

Ontology as Code
type: Concept
type: DefinedTerm
description: Treating ontologies as source code with compilation, version control, and engineering governance.
definition: Treating ontologies as source code.
in scheme: Ontology as Code Glossary

a12
type: Answer
text: Edward Henry warns the biggest illusion is trying to address upstream problems downstream — turning LLM slop into something real. Ontology-as-code addresses this by formalizing meaning at the source rather than patching it in production. Joseph Macdonald extends this with TODAG: temporal patterns (WhenTTT) that make ontologies revenue-generating assets, not just cost centers.

Plain Text
type: Concept
type: DefinedTerm
description: The storage format for ontologies enabling diffs, branches, and LLM navigation — Turtle for readability, JSON-LD for tooling.
definition: Storage format enabling version control and LLM editing.
in scheme: Ontology as Code Glossary

Bas van der Raadt
type: Person
description: Commenter on Tony Seale's ontology-as-code post.

Why plain text for ontologies?
type: Question
accepted answer: a3
text: Why should ontologies live in plain text?

Enable LLM-Mediated Editing
type: HowToStep
description: Use AI Agents like Claude Code with appropriate skills to read, navigate, and edit ontology source files. Kingsley Idehen: ask the agent to express worldviews in your preferred notation. The Semantic Web stack + LLMs form a natural ecosystem.
is part of: Adopting Ontology as Code
position: 5

NAICS 541511
type: DefinedTerm
description: Custom Computer Programming Services — the NAICS classification encompassing ontology engineering, knowledge graph design, and semantic technology consulting.
term code: 541511

Ontology as Code FAQ
type: FAQPage
description: Frequently asked questions about treating ontologies as source code — spanning compilation, version control, LLM integration, decision ontologies, and executable approaches.
has part: Why should ontologies be treated as source code?
has part: What does 'compile, not just parse' mean?
has part: Why plain text for ontologies?
has part: How do LLMs change ontology management?
has part: What is a decision ontology?
has part: What is McOntology?
has part: How does the Semantic Web stack relate to ontology-as-code?
has part: What's wrong with putting ontologies in database tables?
has part: How do you bridge tables to ontology code?
has part: Can ontologies be executable?
has part: Who owns the ontology in an organization?
has part: What is the upstream/downstream gap in AI?
is part of: Your ontology is source code for your meaning.
main entity: Why should ontologies be treated as source code?
main entity: What does 'compile, not just parse' mean?
main entity: Why plain text for ontologies?
main entity: How do LLMs change ontology management?
main entity: What is a decision ontology?
main entity: What is McOntology?
main entity: How does the Semantic Web stack relate to ontology-as-code?
main entity: What's wrong with putting ontologies in database tables?
main entity: How do you bridge tables to ontology code?
main entity: Can ontologies be executable?
main entity: Who owns the ontology in an organization?
main entity: What is the upstream/downstream gap in AI?

CLEARED Platform
type: DefinedTerm
description: Honorio J. Padrón III's platform that sits above the semantic layer to govern the grammar of enterprise action — operationalizing decision ontologies.

Compile
type: Concept
type: DefinedTerm
description: The build step that checks an ontology for logical contradictions and unexpected entailments — breaking the build on failure.
definition: Build step for checking logical consistency.
in scheme: Ontology as Code Glossary

commentGauravMalhotra
type: Comment
author: Gaurav Malhotra
is part of: Comments and Discussion
text: Comment text not captured in LinkedIn guest view.

Bind to a Backend RDF DBMS
type: HowToStep
description: Copy ontology files to a folder transparently bound to a Virtuoso or similar quad/triple store via WebDAV. Filesystem changes automatically propagate to the live knowledge graph. See linkeddata.uriburner.com/DAV/demos/daas/ for live demos.
is part of: Adopting Ontology as Code
position: 6

Compile — Not Just Parse
type: Ontology Pillar
type: DefinedTerm
description: An ontology should compile. A build should break on contradictions or unexpected entailments. An absent entailment is a test failure, not a curiosity discovered six months later in production.

Ontology as Code Glossary
type: ConceptScheme
type: DefinedTermSet
description: Key terms from the ontology-as-code discussion, including contributions from all 14 commenters.
has defined term: Ontology as Code
has defined term: Compile
has defined term: Plain Text
has defined term: Governance
has defined term: RDF-Turtle
has defined term: LLM
has defined term: Decision Ontology
has defined term: Semantic Web Stack
has defined term: Knowledge Graph
has defined term: McOntology
has defined term: Pydantic-Executable Ontology
has defined term: Temporal Objective-Directed Acyclic Graph (TODAG)
is part of: Your ontology is source code for your meaning.

Description Logic
type: DefinedTerm
description: The formal logical foundation for OWL ontologies. Jacob Friedman notes OWL is based on Description Logic and calls for a certifiable normalization standard.

Gaurav Malhotra
type: Person
description: Commenter on Tony Seale's ontology-as-code post.

Kyle Tobin
type: Person
description: Advocate for Pydantic-executable ontologies — entities that conduct their own behavior within application architecture.

commentBasVanDerRaadt
type: Comment
author: Bas van der Raadt
is part of: Comments and Discussion
text: Comment text not captured in LinkedIn guest view.

Tony Seale
type: Person
description: Knowledge Graph Engineer, author of 'The Knowledge Graph Guys' newsletter, advocate for ontology-as-code practices.
interaction statistic:
  interaction type: FollowAction
  user interaction count: 41470

Olivier Rey
type: Person
description: Argues ontology is a hypergraph — code is a tree but ontology is a graph.

Honorio J. Padrón III
type: Person
description: Creator of CLEARED platform for governing the grammar of enterprise action through decision ontologies.

How do LLMs change ontology management?
type: Question
accepted answer: a4
text: How do LLMs change ontology management?

a8
type: Answer
text: Tony Seale: You wouldn't write application code in a database table. Thomas Smith adds: relational databases index binary trees — two dimensions only. Ontologies need triples for three dimensions. Graphs handle circular references that choke SQL. Stepan Karandin: the relational model is the worst kind of normalization for ontology.

Jacob Friedman
type: Person
description: Semantic reasoning specialist with expertise in conceptual graphs, RuleML, and description logic normalization.

Define Decision Ownership and Make It Executable
type: HowToStep
description: Model who owns each decision, what triggers it, and what action it generates (Honorio J. Padrón III). Consider Pydantic for executable entities (Kyle Tobin) or transpilation to class libraries (Robert Sanderson). Consider TODAG temporal patterns for revenue-generating ontologies (Joseph Macdonald). Apply code governance to decisions — break the build when authority is undefined.
is part of: Adopting Ontology as Code
position: 7

Mark Pippins
type: Person
description: Commenter on Tony Seale's ontology-as-code post.

commentKingsley
type: Comment
author: Kingsley Uyi Idehen
date created: 2026-05-21
is part of: Comments and Discussion
is part of: Featured Insight: LLMs + Semantic Web — A Natural Ecosystem
text: Agreed. Ontology management is a classic files-and-filesystem interaction pattern. RDF-Turtle is very much human-readable shorthand but lacked tooling support. Today the Semantic Web stack gels naturally with LLMs and AI Agents. Ask an AI Agent to express worldviews in whatever notation you prefer, save to a file, and copy to a folder bound to a backend RDF DBMS. LLM-powered Agents with Skills make this process a zillion times easier. I will use this post to demonstrate how I've used this approach to create the demo showcases at linkeddata.uriburner.com/DAV/demos/daas/

Industry Context
type: ArticleSection
has part: knowledgeEngineeringVertical
is part of: Your ontology is source code for your meaning.

Can ontologies be executable?
type: Question
accepted answer: a10
text: Can ontologies be made executable?

Your ontology is source code for your meaning.
type: SocialMediaPosting
about: Ontology as Code
about: Compile — Not Just Parse
about: Live in Plain Text
about: Governed Like Code
about: McOntology
about: The Knowledge Graph Guys
about: Linked Art
about: Description Logic
about: Pydantic-Executable Ontology
about: Temporal Objective-Directed Acyclic Graph (TODAG)
about: CLEARED Platform
abstract: Tony Seale argues ontologies should be treated as source code, not database tables — built on three pillars: compilation (breaking the build on contradictions), plain-text version control (diffs, branches, PRs), and code governance discipline. The post sparked a 45-comment discussion with 19 distinct contributors. Kingsley Idehen anchored the response by demonstrating how LLMs and the Semantic Web stack gel naturally, making ontology management dramatically easier with AI Agents and skills. Other notable threads: Veronika Heimsbakk on Python extraction, Honorio J. Padrón III on decision ontologies, Robert Sanderson on transpilation, Kyle Tobin on Pydantic-executable ontologies, and Joseph Macdonald on temporal objective-directed acyclic graphs.
author: Tony Seale
comment: commentKingsley
comment: commentVeronika
comment: commentJacobFriedman
comment: commentRobertSanderson
comment: commentGaborCsepregi
comment: commentHarish
comment: commentJosephMacdonald
comment: commentMarkODonovan
comment: commentKyleTobin
comment: commentHonorio
comment: commentStepan
comment: commentEdwardHenry
comment: commentOlivierRey
comment: commentThomasSmith
comment: commentMarkPippins
comment: commentAslamAhamed
comment: commentGauravMalhotra
comment: commentMichaelGraham
comment: commentBasVanDerRaadt
date modified: 2026-05-22
date published: 2026-05-21
has part: The Three Pillars of Ontology as Code
has part: Ontology as Code FAQ
has part: Ontology as Code Glossary
has part: Adopting Ontology as Code
has part: Comments and Discussion
has part: Industry Context
has part: Featured Insight: LLMs + Semantic Web — A Natural Ecosystem
interaction statistic:
  interaction type: LikeAction
  user interaction count: 400
interaction statistic:
  interaction type: CommentAction
  user interaction count: 45
name: Did you start building your ontology as a set of rows in a custom database table?
was generated by: kg-generator skill v2
was generated by: rdf-infographic-skill v2

a2
type: Answer
text: A build should break on contradictions or unexpected entailments. An absent entailment is a test failure, not a curiosity discovered six months later in production. This catches logical errors at build time rather than in production.

Why should ontologies be treated as source code?
type: Question
accepted answer: a1
text: Why should ontologies be treated as source code?

What's wrong with putting ontologies in database tables?
type: Question
accepted answer: a8
text: What is wrong with putting ontologies in database tables?

Knowledge Engineering Industry
type: Class
subclass of: Industry

commentJacobFriedman
type: Comment
author: Jacob Friedman
date created: 2026-05-21
is part of: Comments and Discussion
text: References conceptual graphs, Harold Boley, and RuleML. Notes OWL is based on Description Logic and asks: 'Can anyone point us to a standards body with a certifiable normalization of Description Logic for OWL?'

What is McOntology?
type: Question
accepted answer: a6
text: What is McOntology?

commentHonorio
type: Comment
author: Honorio J. Padrón III
is part of: Comments and Discussion
text: Operational ontologies describe what exists. Decision ontologies describe what the enterprise does — who owns each decision, what triggers it, what action it generates. An operational ontology makes data legible. A decision ontology makes the enterprise executable. The decision ontology is source code for your will to act. His platform CLEARED sits above the semantic layer to govern the grammar of enterprise action.

Store in Plain Text (Turtle or JSON-LD)
type: HowToStep
description: Save your ontology as an RDF-Turtle or JSON-LD file. Turtle for human readability and LLM navigation; JSON-LD for tooling compatibility. This enables diffs, branches, and blame.
is part of: Adopting Ontology as Code
position: 2

Version Control with Git
type: HowToStep
description: Commit your ontology files to Git. Use branches for ontology changes, pull requests for review, and blame for provenance tracking. Governance with standard engineering discipline.
is part of: Adopting Ontology as Code
position: 4

kg-generator skill v2
type: SoftwareApplication
description: Generated this enhanced RDF-Turtle Knowledge Graph (Edition 2) from the LinkedIn post and its 14-comment discussion thread.

Comments and Discussion
type: ArticleSection
description: 19 distinct contributor threads responding to Tony Seale's ontology-as-code thesis — spanning LLM integration, decision ontologies, Pydantic executability, temporal hypergraphs, transpilation, and the upstream/downstream AI gap.
has part: commentKingsley
has part: commentVeronika
has part: commentJacobFriedman
has part: commentRobertSanderson
has part: commentGaborCsepregi
has part: commentHarish
has part: commentJosephMacdonald
has part: commentMarkODonovan
has part: commentKyleTobin
has part: commentHonorio
has part: commentStepan
has part: commentEdwardHenry
has part: commentOlivierRey
has part: commentThomasSmith
has part: commentMarkPippins
has part: commentAslamAhamed
has part: commentGauravMalhotra
has part: commentMichaelGraham
has part: commentBasVanDerRaadt
is part of: Your ontology is source code for your meaning.

LLM
type: Concept
type: DefinedTerm
description: Large Language Model — AI systems that can read, navigate, and edit ontology source files directly. When paired with skills and bound to a backend RDF DBMS, they enable natural-language-driven ontology management.
definition: Large Language Model for ontology interaction.
in scheme: Ontology as Code Glossary

Robert Sanderson
type: Person
description: Linked Art contributor demonstrating ontology-to-code transpilation in production for cultural heritage data.

How does the Semantic Web stack relate to ontology-as-code?
type: Question
accepted answer: a7
text: How does the Semantic Web stack relate to ontology-as-code?

Joseph Macdonald
type: Person
description: Proposes TODAG hypergraph approach — When-Then-Then-Then patterns for temporal, revenue-generating ontologies.

What does 'compile, not just parse' mean?
type: Question
accepted answer: a2
text: What does 'compile, not just parse' mean?

knowledgeEngineeringVertical
type: Knowledge Engineering Industry
about: NAICS 541511
description: Custom computer programming services — including ontology engineering, knowledge graph design, and semantic technology consulting.
naics: 541511
has automation readiness: High
has labor TAM: ~80B

Governed Like Code
type: Ontology Pillar
type: DefinedTerm
description: Ontologies should be governed with standard engineering discipline — version control, code review, and CI/CD pipelines applied to meaning itself.

Who owns the ontology in an organization?
type: Question
accepted answer: a11
text: Who owns the ontology in an organization?

What is the upstream/downstream gap in AI?
type: Question
accepted answer: a12
text: What is the upstream/downstream gap in AI?

Aslam Ahamed
type: Person
description: Commenter on Tony Seale's ontology-as-code post.

a10
type: Answer
text: Kyle Tobin argues for Pydantic-defined ontologies where entities are executable — 'they don't just describe their own behavior. They conduct it too!' Robert Sanderson demonstrates this with Linked Art's transpilation from RDFS+OWL into Python class libraries. Both approaches embed ontology into application architecture rather than smearing it across components.

commentVeronika
type: Comment
author: Veronika Heimsbakk
date created: 2026-05-21
interaction statistic:
  interaction type: LikeAction
  user interaction count: 14
is part of: Comments and Discussion
text: Hear, hear! Getting ontology from tables into code is easy with four lines of Python.

Decision Ontology
type: Concept
type: DefinedTerm
description: An ontology describing who owns each decision, what triggers it, and what action it generates — making the enterprise executable rather than merely legible. Honorio J. Padrón III: 'source code for your will to act.'
definition: Ontology describing enterprise decisions and actions.
in scheme: Ontology as Code Glossary

McOntology
type: Concept
type: DefinedTerm
description: Commoditized, fast-food approach to ontology — mass-produced rather than carefully engineered. The antithesis of ontology-as-code.
definition: Commoditized fast-food ontology approach.
in scheme: Ontology as Code Glossary

a4
type: Answer
text: Kingsley Idehen (anchor commentary): The Semantic Web stack gels naturally with LLMs and AI Agents. Users can ask an AI Agent to express worldviews in any notation, save to a file, and copy to a folder bound to a backend RDF DBMS. LLM-powered Agents with Skills make this 'a zillion times easier.' The demo showcases at linkeddata.uriburner.com/DAV/demos/daas/ are live examples of this filesystem-to-quad-store pipeline.

commentMichaelGraham
type: Comment
author: Michael Graham
is part of: Comments and Discussion
text: Comment text not captured in LinkedIn guest view.

Temporal Objective-Directed Acyclic Graph (TODAG)
type: DefinedTerm
description: Joseph Macdonald's hypergraph approach for treating ontologies as revenue-generating assets — WhenTTT (When-Then-Then-Then) patterns, not just IFTTT.

Knowledge Graph
type: Concept
type: DefinedTerm
description: A graph-structured data model connecting entities through typed relationships — the runtime instantiation of ontologies, now manageable via plain-text files and LLM agents.
definition: Graph-structured data model from ontologies.
in scheme: Ontology as Code Glossary

commentOlivierRey
type: Comment
author: Olivier Rey
is part of: Comments and Discussion
text: I would rather say: an ontology is a hypergraph. Code is not a graph but a tree.

kingsleyInsight
type: Commentary Thread
type: Comment
author: Kingsley Uyi Idehen
date created: 2026-05-21
is part of: Comments and Discussion
is part of: Featured Insight: LLMs + Semantic Web — A Natural Ecosystem
text: Ontology management is a classic files-and-filesystem interaction pattern. RDF-Turtle is very much human-readable shorthand but lacked tooling support. Today the Semantic Web stack gels naturally with LLMs and AI Agents. Ask an AI Agent to express worldviews in whatever notation you prefer, save to a file, and copy to a folder bound to a backend RDF DBMS. LLM-powered Agents with Skills make this process a zillion times easier.
featured insight: true

What is a decision ontology?
type: Question
accepted answer: a5
text: What is a decision ontology?

a11
type: Answer
text: Harish Iyer frames this as one of the most consequential product decisions a company will make. The ontology guardian role sits at the intersection of engineering, design, and product — a decision owner who maintains the language of the company. Context switching is replaced by context expansion.

Stepan Karandin
type: Person
description: Information theorist who views ontology as information — databases and code are mere formats.

McOntology
type: DefinedTerm
description: A term coined by Tony Seale for commoditized, fast-food approaches to ontology — mass-produced rather than carefully engineered artifacts.

commentJosephMacdonald
type: Comment
author: Joseph Macdonald
is part of: Comments and Discussion
text: WhenTTT, not only IFTTT. Temporal Objective-Directed Acyclic Graphs (TODAG) as a hypergraph approach for treating ontologies as revenue-generating assets.

Ontology Is Code Ontology (Edition 2)
type: Ontology
description: Enhanced lightweight ontology modeling Tony Seale's thesis that ontologies are source code for meaning — not database tables — and the multi-threaded community discussion it sparked on LinkedIn. Edition 2 adds Jacob Friedman, Gabor Csepregi, Joseph Macdonald, Kyle Tobin commentaries and features Kingsley Idehen's LLM + Semantic Web synergy insight as the anchor response.
version: 2.0
comment: Edition 2: Models the three pillars, 19 comment threads, 7-step adoption guide, 12 FAQs, 12 glossary terms, and industry context. Kingsley Idehen's LLM-semantic-web synergy featured as anchor commentary.

a1
type: Answer
text: Because ontologies express formal logic and axioms — not database rows. They should compile, live in plain text for version control, and be governed with engineering discipline. Tony Seale: 'Your ontology is source code for your meaning.'

Temporal Objective-Directed Acyclic Graph (TODAG)
type: Concept
type: DefinedTerm
description: Joseph Macdonald's hypergraph approach using WhenTTT (When-Then-Then-Then) patterns for temporal, revenue-generating ontologies — treating ontologies as assets, not cost centers.
definition: Temporal hypergraph for revenue-generating ontologies.
in scheme: Ontology as Code Glossary

Pydantic-Executable Ontology
type: DefinedTerm
description: Kyle Tobin's approach: define ontologies in Pydantic so entities are executable — they don't just describe their own behavior, they conduct it.