Development of OWL Structure for Recommending Database Management Systems (DBMS)

Abstract

This research focuses on the development of an OWL (Web Ontology Language) structure designed specifically for recommending Database Management Systems (DBMS). The proliferation of various types of DBMSs and their diverse features pose a challenge for users seeking optimal choices based on specific requirements. OWL provides a standardized framework for representing knowledge and semantics, making it suitable for modeling the complex relationships and characteristics of DBMSs. The methodology involves defining OWL classes and properties to capture essential attributes such as data model, scalability, performance, security features, and compatibility with different operating systems and programming languages. Additionally, the ontology incorporates user preferences and requirements as input to refine the recommendations. The implementation includes the creation of an OWL ontology populated with information about existing DBMSs, their capabilities, and user reviews. Reasoning mechanisms are employed to infer relationships and derive recommendations based on the user's specified criteria. Evaluation of the OWL structure involves testing its effectiveness in accurately recommending suitable DBMSs compared to traditional methods. Metrics such as recommendation accuracy, coverage of DBMS features, and user satisfaction will be used to assess the performance of the ontology-based recommendation system. The outcomes of this research are expected to provide valuable insights into the application of semantic technologies, specifically OWL, in enhancing the selection process of DBMSs. By leveraging structured knowledge representation, the developed OWL structure aims to facilitate informed decision-making and improve the efficiency of DBMS selection for diverse applications and user requirements.