An Approach For Transforming of Relational Databases to OWL Ontology

TL;DR

This paper presents a method for automatically transforming relational databases into OWL ontologies, enhancing semantic expressiveness and enabling dynamic knowledge representation through components like triggers.

Contribution

It introduces a novel approach that leverages database components, including triggers, to improve ontology construction from relational data.

Findings

Enhanced semantic power in ontologies derived from databases

Increased expressiveness by incorporating database triggers

Automated process reduces manual effort in ontology creation

Abstract

Rapid growth of documents, web pages, and other types of text content is a huge challenge for the modern content management systems. One of the problems in the areas of information storage and retrieval is the lacking of semantic data. Ontologies can present knowledge in sharable and repeatedly usable manner and provide an effective way to reduce the data volume overhead by encoding the structure of a particular domain. Metadata in relational databases can be used to extract ontology from database in a special domain. According to solve the problem of sharing and reusing of data, approaches based on transforming relational database to ontology are proposed. In this paper we propose a method for automatic ontology construction based on relational database. Mining and obtaining further components from relational database leads to obtain knowledge with high semantic power and more expressiveness. Triggers are one of the database components which could be transformed to the ontology model and increase the amount of power and expressiveness of knowledge by presenting part of the knowledge dynamically