Catholic Semantic Canon

This repository contains a formal ontology designed to model the hierarchical and relational structure of the Catholic Deposit of Faith. It maps the interdependence of Sacred Scripture, Sacred Tradition, and the Magisterium, providing a semantic framework for how these sources are transmitted and interpreted.

📖 Overview

The Catholic Semantic Canon moves beyond a static bibliography. It provides a machine-readable logic for the "Living Tradition", capturing not just what the sources are, but how they relate to one another in terms of authority, chronology, and theological weight.

🛠 Core Objectives

• Hierarchical Mapping: Defining the relationship between primary revelation and secondary authoritative commentary.
• Interdependence: Modeling how the Church’s Magisterium interprets Scripture and how Tradition sustains both.
• Contextual Use: Tracking the development of doctrine and the application of sources within liturgical and canonical contexts.
• Semantic Interoperability: Enabling theological data to be queried using standardized formats (such as OWL or RDF).

🗂 Key Components

Component	Description
Sacred Scripture	The written Word of God, categorized by canon, genre, and testament.
Sacred Tradition	The oral and lived transmission of faith, including Patristics and Liturgy.
The Magisterium	The teaching authority (Papal Encyclicals, Conciliar Documents) and their levels of certainty.
Relational Logic	Predicates that define "Interpretation," "Clarification," and "Succession."

🚀 Getting Started

The primary "source of truth" for this ontology is hosted on WebProtégé. To ensure data integrity and collaborative consistency, all structural edits and maintenance are managed through that platform.

• Access the Model: Catholic OS Ontology on WebProtégé
• Contributions: Contributors should request access via the WebProtégé link above. All edits to classes and relationships should be made directly in the instance.
• Issue Tracking: Please use the GitHub Issues tab to propose major structural changes or discuss ontological definitions.
• Versioning: Versioning and exports are handled by the maintainers via WebProtégé. Direct Pull Requests to the ontology files in this repo will generally not be accepted.

🔍 Running SPARQL Queries

The queries/ folder contains sample SPARQL queries for exploring the ontology. These queries can be run using various tools.

Quick Start with Example Projects

The examples/ folder contains ready-to-run projects for both Python and Java:

Python (rdflib) — Full documentation

cd examples/python

# Using python venv
python3 -m venv venv
source venv/bin/activate            # Windows: venv\Scripts\activate
pip install -r requirements.txt

# Or using uv (faster)
uv venv && source .venv/bin/activate && uv pip install -r requirements.txt

# Run queries
python query_runner.py              # Interactive menu
python query_runner.py 01           # Run specific query
python query_runner.py --list       # List all queries

Java (Apache Jena / Maven) — Full documentation

cd examples/java
mvn compile exec:java                           # Interactive menu
mvn compile exec:java -Dexec.args="01"          # Run specific query
mvn compile exec:java -Dexec.args="--list"      # List all queries

# Or build an executable JAR
mvn package
java -jar target/semantic-canon-query-runner-1.0.0.jar

Using Apache Jena (Command Line)

If you have Apache Jena installed globally, use the arq command. See the Java example documentation for installation instructions.

# Run a query against the OWL file
arq --data=sources/ontology-semantic-canon.owl --query=queries/01-list-all-classes.rq

# Run against the Turtle file
arq --data=sources/ontology-semantic-canon.ttl --query=queries/03-find-church-hierarchy-roles.rq

Using rdflib (Python) Directly

from rdflib import Graph

# Load the ontology (use OWL format for best compatibility)
g = Graph()
g.parse("sources/ontology-semantic-canon.owl", format="xml")

# Run a query
with open("queries/01-list-all-classes.rq") as f:
    query = f.read()

for row in g.query(query):
    print(row)

Note: The ontology contains 120,000+ triples. See the Python example documentation for caching strategies and known compatibility issues with Python 3.12.

Using a Triple Store

For larger-scale querying, load the ontology into a triple store:

• Apache Jena Fuseki: Upload the OWL/TTL file and use the built-in SPARQL endpoint
• GraphDB: Import the ontology and query via the Workbench UI
• Blazegraph: Load data and query through the web interface

Using Protégé

1. Open the ontology in Protégé
2. Go to Window → Tabs → SPARQL Query
3. Paste any query from the queries/ folder and execute

Available Queries

Query	Description
01-list-all-classes.rq	List all classes with labels and definitions
02-list-object-properties.rq	List object properties with domains/ranges
03-find-church-hierarchy-roles.rq	Find Pope, Cardinal, Bishop, Priest roles
04-find-sacrament-concepts.rq	Find sacrament-related concepts
05-class-hierarchy.rq	Display subclass relationships
06-find-religious-orders.rq	Find religious orders and institutes
07-find-juridical-structures.rq	Find Diocese, Parish, Holy See, etc.
08-authority-properties.rq	Find authority/jurisdiction concepts
09-provenance-relationships.rq	Track document origins and versions
10-legal-actions.rq	Find FOLIO legal action properties
11-search-by-keyword.rq	Template for full-text keyword search
12-ontology-statistics.rq	Get counts of classes/properties
13-find-liturgical-concepts.rq	Find Mass, Liturgy, Rite concepts
14-find-canon-law-documents.rq	Find Canon, Decree, Encyclical types
15-construct-label-graph.rq	CONSTRUCT query for vocabulary extraction

Note: Additional semantic queries optimized for different SPARQL engines are available in queries/jena/ and queries/rdflib/. See Python documentation and Java documentation for details.