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

arXiv: https://arxiv.org/abs/1611.02816 · HTML: https://mlsanity.com/paper/1611.02816/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Nov 2016.

## Built on by (most cited first, 1 of 1)

- [Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology using Large Language Models -- A Case in Optimizing Intermodal Freight Transportation](https://mlsanity.com/paper/2405.19255/) (2024)

## Abstract (arXiv)

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.