OWLAPY: A Pythonic Framework for OWL Ontology Engineering

TL;DR

OWLAPY is a versatile Python framework that simplifies OWL ontology engineering by integrating reasoners, supporting multiple formats, and enabling ontology generation from natural language using LLMs.

Contribution

It introduces a comprehensive Python-based tool that combines reasoning, format conversion, and natural language integration for OWL ontology development.

Findings

Supports native and external reasoners for OWL 2

Enables conversion between OWL formats and expressions

Facilitates ontology generation from natural language using LLMs

Abstract

In this paper, we introduce OWLAPY, a comprehensive Python framework for OWL ontology engineering. OWLAPY streamlines the creation, modification, and serialization of OWL 2 ontologies. It uniquely integrates native Python-based reasoners with support for external Java reasoners, offering flexibility for users. OWLAPY facilitates multiple implementations of core ontology components and provides robust conversion capabilities between OWL class expressions and formats such as Description Logics, Manchester Syntax, and SPARQL. It also allows users to define custom workflows to leverage large language models (LLMs) in ontology generation from natural language text. OWLAPY serves as a well-tested software framework for users seeking a flexible Python library for advanced ontology engineering, including those transitioning from Java-based environments. The project is publicly available on GitHub at https://github.com/dice-group/owlapy and on the Python Package Index (PyPI) at https://pypi.org/project/owlapy/ , with over 50,000 downloads at the time of writing.