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.

Extending ONTAgri with Service-Oriented Architecture towards Precision Farming Application

“…Recent ontologies proposed in the research literature are [1,2,[8][9][10]. A short description of these contributions is as follows.…”

“…In [9], authors proposed a framework that matches evaluation approaches that are gold-standard, application-based, criteria-based, and data-driven to different ontology purposes that share vocabularies and integrate data, system interoperability, knowledge search and exploration, and decision support. In [10], the authors developed SAAONT, which is specifically focused on the farmers of the Saudi Arabia region. Previous ontologies did not support the required level of knowledge to farmers.…”

“…In future research, it can be implemented on other agriculture ontologies. In [10], authors only targeted Saudi Arabia and created ontology for the Arabic region; there are several ontologies in different languages, but recognition of the Arabic language is not common among farmers around the world, so this ontology is limited to the Arabic region only.…”

RustOnt: An Ontology to Explain Weather Favorable Conditions of the Coffee Rust

“…Several research studies have documented the use of ontologies for agricultural control and monitoring for rice, coffee, and cocoa [15,16]; precision agriculture data [17]; mandarin crop life cycle [18]; coffee supply chain [19]; horticulture [20]; and smart livestock farming [21]. Only two of these studies are directly related to coffee cultivation and focus on modeling available pest and disease data.…”