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

Jedrzej Potoniec, Piotr Jakubowski, Agnieszka Lawrynowicz

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 Prot´eg´e plugin implementing the algorithm, to support ontology engineers in their daily modelling work.

Full Text: Untitled
Type of Paper: Research Paper
Keywords: linked data, on-line linked data mining, ontology learning, OWL 2 EL, RDF Data Shapes, Protege plugin 2010 MSC: 68T05, 68T10, 68T27, 68T30
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