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ontology

Designs RDFS and OWL 2 ontologies, taxonomies, and controlled vocabularies with reasoner validation.

Updated Aug 28, 2026
Search Tags:#knowledge graph#ontology#taxonomy#semantic modeling#skos#owl 2#rdfs
One-click install
npx skills add https://github.com/miyake-san/sogo-agent-platform --skill ontology-miyake-san
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ontology
Source: https://github.com/miyake-san/sogo-agent-platform/tree/main/skills/experimental/ontology
Command: npx skills add https://github.com/miyake-san/sogo-agent-platform --skill ontology-miyake-san

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Modeling a domain semantically is error-prone: the Open-World Assumption, inferential domain/range semantics, and OWL 2 profile trade-offs trip up even experienced engineers. This Skill guides the design of well-formed, reusable, reasoner-friendly ontologies and controlled vocabularies that validate consistently. ## Core Features & Use Cases - Ontology & Taxonomy Modeling: Define classes, object/datatype properties, axioms, restrictions, and cardinality in RDFS and OWL 2. - Vocabulary Reuse: Extend standard vocabularies like schema.org, SKOS, Dublin Core, and FOAF instead of minting redundant IRIs. - Profile Selection & Validation: Choose the right OWL 2 profile (EL/QL/RL) and validate consistency with Protégé and reasoners like HermiT, Pellet, or ELK. - Use Case: When asked to build a domain model for a knowledge graph, produce competency questions, a Turtle-serialized model with proper disjointness and cardinality axioms, and a reasoner-verified class hierarchy. ## Quick Start Use the ontology skill to design an OWL 2 ontology for a university domain with classes, properties, and competency questions, serialized in Turtle.

Frequently Asked Questions about ontology

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build an ontology for a domain?▼

Follow the Ontology Development 101 methodology: write competency questions, reuse existing vocabularies, enumerate terms, define the class hierarchy, add properties and axioms, create individuals, then validate with a reasoner. Tools like Protégé support the full authoring workflow.

What is the difference between RDFS and OWL 2?▼

RDFS provides basic vocabulary constructs like classes, subclasses, and property domain/range. OWL 2 adds expressive axioms such as disjointness, equivalence, cardinality restrictions, and property characteristics, enabling automated reasoning over the model.

Which OWL 2 profile should I choose: EL, QL, or RL?▼

Choose OWL 2 EL for large class-heavy ontologies like biomedical terminologies, QL for query answering over relational data, and RL for rule-based reasoning over RDF data. Default to plain RDFS when you only need a simple vocabulary.

Why does my OWL ontology not infer what I expect?▼

OWL uses the Open-World Assumption and no Unique Name Assumption, so missing facts are unknown rather than false. Add DisjointClasses or DifferentIndividuals axioms explicitly, and remember domain/range declarations drive inference rather than validation.

Can I reuse schema.org or SKOS in my ontology?▼

Yes, reusing existing vocabularies is recommended over minting new IRIs. Import or extend schema.org for general entity types, SKOS for thesauri and taxonomies, Dublin Core for metadata, and FOAF for people and social relations.

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