🦉 SWOWL — OWL/SWRL Editor

Web editor for OWL ontologies : classes, properties, individuals & SWRL rules. GUI for visual SPARQL queries.

Current version: 1.1.0 — see the CHANGELOG for the full feature list.

Getting started

Prerequisites

• Docker Desktop (Docker Compose included)

Installation

git clone https://github.com/MyShivaRepo/swowl.git
cd swowl
docker compose up --build

Access

Service	URL
Interface	http://localhost:12345
API (Swagger)	http://localhost:8001/docs

First steps

New to SWOWL? The How to start guide walks you step by step through the two ontology wizards:

• New Ontology — start from scratch with an empty ontology.
• Import Ontology — bring in an existing .owl / .ttl / .rdf file to visualise and edit.

Features

• OWL 2 — classes (subClassOf, equivalent, disjoint, restrictions), object/datatype properties (domain, range, characteristics, hierarchies), individuals and assertions.
• Imports — owl:imports: imported entities appear read-only, dimmed, with their prefix.
• SWRL — visual rule editor with live preview.
• SPARQL — visual query builder.
• SKOS — skos: annotations (prefLabel, altLabel, definition…) imported and editable.
• Inference engine — transitivity, restriction inheritance, types via domain/range, inverse, property chains, violation detection… (backend engine, available via the REST API /api/inferences).
• Import / Export — OWL/XML, Turtle, JSON-LD, SWORD (rules import/export).
• Consistent UX — homogeneous filter+tree pickers everywhere, global search, undo/redo, USER/SYSTEM ontology registry.

Persistence

Complete ontologies (OWL + SWRL) are stored as JSON files referenced in ~/.swowl/registry.json. They are reloaded on each startup and remain on the host (outside the container).

Technical architecture

Two Docker containers orchestrated by Compose:

Layer	Stack
Frontend	Nginx — vanilla HTML/CSS/JS (no framework, no build)
Backend	Python 3.11 — FastAPI + Uvicorn, rdflib (RDF parsing/serialization), Pydantic (OWL 2 models)

• Communication — REST API; Nginx serves the static files and proxies /api/ to the backend (Uvicorn, port 8000).
• Model — OWL 2 and SWRL entities are typed with Pydantic models; an rdflib triple store handles RDF import/export.
• Inference — in-house engine (forward chaining) on the backend, available via the REST API (/api/inferences); no dedicated UI tab.

Structure

backend/    FastAPI API, OWL models, triple store, inference/serialization engines
frontend/   index.html, js/ (editors, app, api), css/
exigences/  requirements (specs per tab)