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

Autor: Potoniec, Jedrzej, Jakubowski, Piotr, Ławrynowicz, Agnieszka
Rok vydání: 2017
Předmět:
Druh dokumentu: Working Paper
DOI: 10.1016/j.websem.2017.08.001
Popis: 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.
Databáze: arXiv