Swift Linked Data Miner: Mining OWL 2 EL Class Expressions Directly From On-Line RDF Datasets

Abstract

We present Swift Linked Data Miner, an interruptible algorithm that can directly mine an on-line 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 Protégé plugin implementing the algorithm, to support ontology engineers in their daily modelling work.

Keywords: linked data, on-line linked data mining, ontology learning, OWL 2 EL, RDF Data Shapes, Protege plugin