Convert SQL database schemas into TTL/OWL ontologies.
npx skills add https://github.com/gtheys/pi-my-rifle-ext --skill db-to-ontology
Please help me install this Agent Skill. Skill: db-to-ontology Source: https://github.com/gtheys/pi-my-rifle-ext/tree/main/skills/db-to-ontology Command: npx skills add https://github.com/gtheys/pi-my-rifle-ext --skill db-to-ontology
Converts an existing database schema into a formal ontology (TTL/OWL), enabling semantic modeling, knowledge graphs, and reasoner-ready representations.
Connect a database or paste a CREATE TABLE dump and ask the skill to generate a TTL/OWL ontology from the schema.
High-intent search queries and answers about installing and using this skill.
To convert a database schema into an OWL ontology, you provide connection strings or CREATE TABLE statements, and the tool generates a formal Turtle/OWL semantic model with classes and properties. This transforms relational structures into a reasoner-ready knowledge graph.
Yes, you can generate a knowledge graph from a PostgreSQL or MySQL dump by inputting SQL schema dumps or CREATE TABLE statements. The tool extracts tables, columns, and relationships to produce a structured Turtle/OWL ontology output.
The best way to create a semantic model from SQL tables is introspecting a live database or schema dump to extract keys and relationships. It generates a structured Turtle/OWL ontology with ontological axioms suitable for data integration and querying.
No, you do not need a live database connection to generate a Turtle TTL file. You can simply paste a CREATE TABLE schema dump, and the tool will extract the structural metadata to produce a version-controlled, reasoner-ready ontology.
Yes, this approach supports ontology generation for SQLite and other SQL databases. You can supply connection strings or SQL dumps to produce a formal OWL representation with a configured base URI and scope.
Converting a relational database schema into a formal ontology enables semantic modeling and knowledge graph construction. The resulting Turtle/OWL output provides a reasoner-ready representation with ontological axioms for advanced data integration.
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