Open Access

ARTICLE

An OWL-Based Specification of Database Management Systems

Sabin C. Buraga^1,*, Daniel Amariei¹, Octavian Dospinescu²

1 Alexandru Ioan Cuza University, Faculty of Computer Science, Iasi, 700706, Romania
2 Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, Iasi, 700706, Romania

* Corresponding Author: Sabin C. Buraga. Email:

Computers, Materials & Continua 2022, 70(3), 5537-5550. https://doi.org/10.32604/cmc.2022.021714

Received 12 July 2021; Accepted 17 August 2021; Issue published 11 October 2021

Abstract

In the context of a proliferation of Database Management Systems (DBMSs), we have envisioned and produced an OWL 2 ontology able to provide a high-level machine-processable description of the DBMSs domain. This conceptualization aims to facilitate a proper execution of various software engineering processes and database-focused administration tasks. Also, it can be used to improve the decision-making process for determining/selecting the appropriate DBMS, subject to specific requirements. The proposed model describes the most important features and aspects regarding the DBMS domain, including the support for various paradigms (relational, graph-based, key-value, tree-like, etc.), query languages, platforms (servers), plus running environments (desktop, Web, cloud), specific contexts—i.e., focusing on optimizing queries, redundancy, security, performance, schema vs. schema-less approaches, programming languages/paradigms, and others. The process of populating the ontology with significant individuals (actual DBMSs) benefits from the existing knowledge exposed by free and open machine-processable knowledge bases, by using structured data from Wikipedia and related sources. The pragmatic use of our ontology is demonstrated by two educational software solutions based on current practices in Web application development, proving support for learning and experimenting key features of the actual semantic Web technologies and tools. This approach is also an example of using multiple knowledge from database systems, semantic Web technologies, and software engineering areas.

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Citations