SAAONT: Ontological knowledge-based development to support intelligent decision-making systems for Saudi Arabian agriculture

Abstract

Ontologies have become an essential tool for domain knowledge representation and a core element of many intelligent systems. It considered an appropriate solution to represent complex concepts and relationships within the agricultural domain. Over the last years, there has been an increasing number of undertaken efforts to develop ontology-based agricultural systems. These existing agricultural ontologies may not be sufficient to provide the desired level of information to individual farmers in Arabic regions, i.e. Saudi Arabia. Additional work is therefore needed to focus on building Arabic ontologies to provide the relevant, contextual and scientifically correct information in Arabia. Furthermore, the current practices within the Saudi Arabian agriculture sector are traditional and lack the technological foundations necessary to build and support intelligent, and sustainable technical solutions. Besides the contribution to the body of knowledge, this paper outlines a state-of-art ontological knowledge-based development for the agriculture sector in Saudi Arabia. It proposes an ontology-driven information retrieval system for agriculture in Saudi Arabia (SAAONT). It aims to firstly, structure and standardize agricultural terminology in Arabic and secondly, provide accurate information to decision-makers, to establish a smarter agriculture environment.