Automatic Conversion of Relational Databases into Ontologies: A Comparative Analysis of Prot\'eg\'e Plug-ins Performances

TL;DR

This paper compares two Protégé plug-ins, DataMaster and OntoBase, for automatically converting relational databases into ontologies, analyzing their adherence to mapping principles and performance.

Contribution

It provides a comparative analysis of plug-ins' effectiveness in database-to-ontology conversion, highlighting OntoBase's superior performance.

Findings

OntoBase better adheres to mapping principles than DataMaster.

OntoBase produces more structurally accurate ontologies.

The study offers insights into automatic ontology construction quality.

Abstract

Constructing ontologies from relational databases is an active research topic in the Semantic Web domain. While conceptual mapping rules/principles of relational databases and ontology structures are being proposed, several software modules or plug-ins are being developed to enable the automatic conversion of relational databases into ontologies. However, the correlation between the resulting ontologies built automatically with plug-ins from relational databases and the database-to-ontology mapping principles has been given little attention. This study reviews and applies two Prot\'eg\'e plug-ins, namely, DataMaster and OntoBase to automatically construct ontologies from a relational database. The resulting ontologies are further analysed to match their structures against the database-to-ontology mapping principles. A comparative analysis of the matching results reveals that OntoBase outperforms DataMaster in applying the database-to-ontology mapping principles for automatically converting relational databases into ontologies.