Swift Linked Data Miner: Mining OWL 2 EL class expressions directly from online RDF datasets

TL;DR

Swift Linked Data Miner is an interruptible algorithm that efficiently mines OWL 2 EL class expressions from online RDF datasets, aiding ontology extension with validated axioms and supporting ontology engineers through a Protégé plugin.

Contribution

It introduces a novel interruptible algorithm for direct mining of OWL 2 EL class expressions from online Linked Data sources, with a transformation to RDF Data Shapes and practical Protégé integration.

Findings

Most mined axioms are correct and suitable for ontology extension.

The algorithm efficiently handles large online datasets by partial data download and smart indexing.

The Protégé plugin facilitates practical ontology engineering workflows.

Abstract

In this study, we present Swift Linked Data Miner, an interruptible algorithm that can directly mine an online Linked Data source (e.g., a SPARQL endpoint) for OWL 2 EL class expressions to extend an ontology with new SubClassOf: axioms. The algorithm works by downloading only a small part of the Linked Data source at a time, building a smart index in the memory and swiftly iterating over the index to mine axioms. We propose a transformation function from mined axioms to RDF Data Shapes. We show, by means of a crowdsourcing experiment, that most of the axioms mined by Swift Linked Data Miner are correct and can be added to an ontology. We provide a ready to use Prot\'eg\'e plugin implementing the algorithm, to support ontology engineers in their daily modeling work.