A system whose semantics and behavior are driven by ontology artifacts beyond just RDF syntax snapshots.
Ontology-driven system
A phrase for the role of an ontology in defining what an organization means by customer, order, risk, product, and other core terms.
Source code for meaning
A pattern where highly regular large ontologies are curated in tables and mapped to design patterns.
Table-driven ontology pattern
The distinction between vocabularies, taxonomies, and ontologies raised in the comments.
Vocabulary and taxonomy boundary
Comment by Gauransh Dhruv Tandon
The compile step only bites if axioms have teeth; many enterprise ontologies are descriptive vocabularies in OWL clothing without constraints strict enough for a reasoner to disprove.
Query Construct Workflow
PREFIX ex: <https://www.linkedin.com/posts/tonyseale_did-you-start-building-your-ontology-as-a-share-7463353332565356545-jY54#> PREFIX schema: <http://schema.org/> CONSTRUCT { ex:ontologyAsCode ?p ?o . ?o schema:name ?name . } WHERE { GRAPH <https://linkeddata.uriburner.com/DAV/demos/daas/ontology-is-source-code-tony-seale-gpt5-chat-1.ttl> { ex:ontologyAsCode ?p ?o . OPTIONAL { ?o schema:name ?name } } }
Plain text gives ontology engineers and LLM agents access to files, diffs, branches, blame, pull requests, and review context.
A formal graph of classes, relationships, constraints, and axioms for a domain.
Ontology
Generated RDF, HTML, and Markdown collection for Tony Seale's LinkedIn post about treating ontologies as governed source code.
Ontology Is Source Code Knowledge Graph Collection
Build checks that catch syntax errors, unsatisfiable classes, unexpected entailments, contradictions, and duplicate concepts.
Automated ontology checks
They increase the value of direct source access because an LLM can read, navigate, and edit ontology files like a codebase, instead of only querying an API.
Review ontology changes in pull requests
Use branches, diffs, contextual comments, and approval rules for ontology changes.
Browser automation used to capture visible LinkedIn post content.
Browser Use
The central claim that an ontology is logic and source code for organizational meaning, not a database table.
Ontology is code
An API-based access path for tools and LLMs that should complement, not replace, direct source access.
MCP server
Strict logical axioms that allow a reasoner or compile step to disprove invalid ontology states.
Axioms with teeth
Principal data strategist and researcher; commenter warning about vendors reframing themselves as ontology tools.
Juan Sequeda
Builder of AI systems; commenter on executable ubiquitous language and typed programming models for ontology-backed data.
Gaurav Malhotra
Why is plain text important for ontology work?
Comment by Nicolas Matentzoglu
For huge, highly regular ontologies such as anatomy, biological traits, or chemistry, one can sometimes curate the ontology in a table and map every instance or class to a design pattern that provides the logical modelling.
Query Comment Perspectives
PREFIX schema: <http://schema.org/> PREFIX ex: <https://www.linkedin.com/posts/tonyseale_did-you-start-building-your-ontology-as-a-share-7463353332565356545-jY54#> SELECT ?comment ?authorName ?topicName ?text WHERE { GRAPH <https://linkeddata.uriburner.com/DAV/demos/daas/ontology-is-source-code-tony-seale-gpt5-chat-1.ttl> { ex:commentThread schema:hasPart ?comment . ?comment schema:author ?author ; schema:text ?text ; schema:about ?topic . ?author schema:name ?authorName . ?topic schema:name ?topicName . } } ORDER BY ?authorName ?topicName
Builder and machine learning engineer; commenter on axioms needing enough strictness for compile checks to bite.
Gauransh Dhruv Tandon
Developer concern about persisting objects instead of rows, tables, or documents.
Object-relational impedance mismatch
Using the same engineering controls applied to code: branches, pull requests, reviews, automated checks, releases, and builds.
Author of the LinkedIn post and The Knowledge Graph Guy.
Tony Seale
Maintaining ontology definitions in files to enable diffs, branches, pull requests, blame, and source review.
Plain-text source
14m
Comment by Robert Sanderson
That sounds like it should be a vocabulary or taxonomy rather than an ontology, raising the question of whether vocabularies should be treated as code as well.
Local development environment used for generation and validation.
Codex desktop
A programming model where ontology concepts become daily engineering objects and methods.
Executable ubiquitous language
Enterprise ontologist and CTO; commenter noting that ontology-driven systems involve more than RDF syntax.
Bas van der Raadt
Founder and CEO at OpenLink Software; commenter emphasizing ontology work as a files-and-filesystem interaction pattern.
Kingsley Uyi Idehen
Comment by Stephen Redmond
Turtle is the coding language of choice because it plays nicely with SDLC tools.
Treating ontology source as logic-bearing code that compiles, has tests, and follows engineering governance.
Ontology as code
Review workflow for ontology changes in context.
Pull request review
AI agents that can generate, edit, and manage ontology files when loosely coupled with appropriate skills.
LLM-powered agents
Because it declares organizational meaning using formal logic, relationships, constraints, and axioms; those artifacts need compilation, review, automated checks, and release discipline.
Tools and vendor capabilities for RDF-native authoring, storage, reasoning, and publishing.
RDF-native tooling
Ontology files maintained as source artifacts that support diffs, branches, blame, and pull requests.
Plain-text ontology source
Tony Seale LinkedIn post arguing that ontologies should compile, live in plain text, and be governed like source code.
Did you start building your ontology as rows in a custom database table?
Did you start building your ontology as a set of rows in a custom database table? The instinct is completely understandable. As software engineers we have spent our careers putting things into databases: customers, orders, events. So when the organisation says it needs an ontology, the database is the tool to hand. But please let me suggest a different way of looking at the problem. Because an ontology really is not that kind of artefact. Ontology IS Code. It is where your organisation declares what kinds of things exist, how they relate, and what cannot both be true. It is logic. It is expressive. It is a graph of interrelated concepts that build on one another. Formal logic, expressed as a set of rigorous axioms. So treat it that way. It should compile. Not just parse. Compile. The syntax should be valid. The classes should be satisfiable. The entailments should be the ones you expected. An absent entailment is a test failure, not a curiosity you discover six months later in production. If the model says two things that cannot both be true, the build should break. If a new term silently duplicates an existing concept, the build should break. It should live in plain text. You would not write your application code in a database table. You want files, diffs, branches, blame, pull requests and review in context. All of this is just as true for the classes in your ontology. It is especially true now that we have large language models in the loop. You do not only want the LLM reaching for your ontology through an API or an MCP server. You want it to read, navigate and edit the source directly, exactly the way it works with a codebase. It should be governed like code. Branches. Pull requests. Reviews. Automated checks. Releases. Builds. None of this needs inventing. Your engineering organisation already does all of it, often for code that carries far less conceptual weight. The artefact that decides what your organisation means by a customer, an order, a risk, a product should not be governed less rigorously than the CSS on your marketing site. Compile it. Branch it. Review it. Ship it. Because it is not a table. Not a schema. Your ontology is source code for your meaning.
Resolver and SPARQL endpoint used for entity description and live queries.
URIBurner resolver
Add compile and reasoning checks
Validate syntax, class satisfiability, expected entailments, contradictions, and duplicate concept risks in CI.
Comment by Bas van der Raadt
Ontology as code involves more than producing and processing RDF syntax; an ontology-driven system has more involved and snapshot-based approaches are only part of the story.
Founder at Straitéis AI; commenter describing Turtle as a coding language aligned with SDLC tools.
Stephen Redmond
Comment by Veronika Heimsbakk
If an ontology is in tables, it can be moved into code and iterated from there.
Ontology classes that can have possible instances without logical contradiction.
Satisfiable classes
How do LLMs change ontology engineering?
How should an ontology be governed?
Digital cultural heritage leader at Yale University; commenter distinguishing vocabulary, taxonomy, and ontology as code.
Robert Sanderson
A validation gate where ontology syntax, satisfiability, entailments, contradiction checks, and duplicate concept checks must pass.
Compile gate
What does it mean for an ontology to compile?
A design principle where large language models can read, navigate, and edit ontology source directly like a codebase.
LLM-readable source
Modeling an ontology as rows in a custom table, losing code review, diffs, compilation, and formal reasoning.
Database-table ontology anti-pattern
Co-founder at FlexVertex; commenter asking about object persistence and object-relational impedance mismatch.
Robert Schneider
Expose source and services to LLM agents
Let LLMs navigate source files directly while also providing APIs, MCP tools, SPARQL endpoints, and documentation.
11m
Comment by Kingsley Uyi Idehen
Yes! The creation and management of ontologies, and even instance data, is a classic files-and-filesystem interaction pattern. Before LLMs this was difficult because RDF notations had tradeoffs: Turtle was human-readable but lacked tooling support, JSON-LD had more tooling support but was less readable, and RDF/XML was challenged on both fronts. Today, the Semantic Web stack gels naturally with LLMs and AI Agents. An agent can express a conceptualization in the notation you prefer and save it to a file; on suitable platforms those files can be copied to a folder transparently bound to a backend RDF DBMS for updating the triple or quad store.
It means syntax is valid, classes are satisfiable, expected entailments are present, contradictions fail the build, and duplicate concepts are detected before release.
An overview of RDF-native tooling and what major vendors support is relevant to the ontology-as-code discussion.
Comment by Juan Sequeda
This is why everyone should be careful with new tools and vendors that are now reframing themselves as ontology tools.
Query Core Practices
PREFIX schema: <http://schema.org/> PREFIX ex: <https://www.linkedin.com/posts/tonyseale_did-you-start-building-your-ontology-as-a-share-7463353332565356545-jY54#> SELECT ?practice ?name ?description WHERE { GRAPH <https://linkeddata.uriburner.com/DAV/demos/daas/ontology-is-source-code-tony-seale-gpt5-chat-1.ttl> { ex:ontologyAsCode ex:hasComponent ?practice . ?practice schema:name ?name ; schema:description ?description . } } ORDER BY ?name
Publishing platform and source location for the social post.
LinkedIn
The gap between an ontology codebase's current engineering quality and the value the organization can derive from AI.
Ontology technical debt
Independent consultant in semantic technology and knowledge engineering; commenter on large regular ontologies curated from tables.
Nicolas Matentzoglu
RDF database and Linked Data server behind URIBurner.
OpenLink Virtuoso
Differences among Turtle, JSON-LD, and RDF/XML in human readability and tooling support.
RDF notation tradeoffs
Skill used for RDF-backed HTML and Markdown generation.
rdf-infographic-skill
Move ontology definitions into source files
Use RDF/Turtle, OWL, SHACL, or another text-based ontology source format that supports version control.
Automated validation that catches invalid syntax, unsatisfiable classes, missing entailments, contradictions, and duplicates.
Comment by Andrea Mazzoni
The technical debt of the ontology codebase and associated DevOps measures the gap between current state and the value a company can derive from AI.
Ontology governance using branches, pull requests, reviews, automated checks, releases, and builds.
Governed like code
Publish versioned ontology releases
Package, tag, and document ontology releases so downstream systems and agents know which meaning contract they use.
Comment by Gaurav Malhotra
Ontology should not hide in an EAV table. It should compile, diff, branch, and fail CI when meaning breaks. The real test is executable ubiquitous language rather than a semantic artifact only specialists maintain.
Why should an ontology be treated as code?
A platform pattern where files copied to a folder update a backend RDF DBMS triple or quad store.
Folder-to-quad-store binding
Knowledge graph specialist; commenter pointing to RDF-native tooling and table-to-code workflows.
Veronika Heimsbakk
LLM interface used to generate this collection.
gpt5-chat
The view that RDF Turtle fits SDLC-oriented ontology engineering because it works well with code tools.
Turtle as coding language
Comment by Robert Schneider
A question about developers trying to eliminate object-relational impedance mismatch by persisting data as objects instead of rows in tables or documents.
Skill used for RDF generation.
kg-generator
Kingsley Idehen's framing of ontology and instance-data management as a classic source-file workflow.
Files-and-filesystem pattern
Visible LinkedIn comments captured from the source post, starting with Kingsley Uyi Idehen's comment.
LinkedIn discussion thread
Chief data officer; commenter linking ontology codebase technical debt to AI value realization.
Andrea Mazzoni
Query Compile Gates
PREFIX schema: <http://schema.org/> PREFIX ex: <https://www.linkedin.com/posts/tonyseale_did-you-start-building-your-ontology-as-a-share-7463353332565356545-jY54#> SELECT ?check ?name ?description WHERE { GRAPH <https://linkeddata.uriburner.com/DAV/demos/daas/ontology-is-source-code-tony-seale-gpt5-chat-1.ttl> { ex:compileGate ex:tests ?check . ?check schema:name ?name ; schema:description ?description . } } ORDER BY ?name
A formal graph of interrelated concepts, relationships, constraints, and axioms.
Risk that new tools or vendors reposition themselves as ontology tooling without adequate semantic rigor.
Ontology-tool vendor reframing risk
The role of ontology as the formal source for what organizational concepts mean.
Inferences that the ontology should produce and that can be tested like build expectations.
Expected entailments