Modeling Competency Questions Based Ontology for the Domain of Maize Crop: SIMcOnto

Abstract

In this present time, there is rapid increase of various forms and struc-tures of information across different domains of real world; for instance, agricul-ture. Because of this development, information is readily available; however, to retrieve the relevant information becomes a research issue to contend with. This identified research issue is on one hand attributed to the unstructured representa-tion of data and on the other hand attributed to the problem of word mismatch. Consequently, and in lieu of this; to retrieve relevant soils and irrigations data for maize crop in a more efficient structure becomes a challenge. Therefore, this re-search work aims to model soils and irrigations data for maize crop ontologically; which is christened as SIMcOnto. In other to achieve this objective, Ontology which is a data modeling technique for complex knowledge representation is ex-ploited. At the end, rule based Ontology is developed using the combined meth-odologies approach and written using OWL2 (Web Ontology Language) in the syntax of RDF/XML. The rules leverage on the validated Competency Questions (CQs) which are modeled in First Order Logic (FOL). During the course of the ontology development, the terminologies and the semantic rules are validated and verified by the domain experts and evaluation techniques. Therefore, the pro-posed SIMcOnto provides a machine represented knowledge-based modeling for soils and irrigations knowledge of maize crop. It is promising in retrieving a more precise and efficient information.