@article {10.3844/jcssp.2026.1060.1072,
article_type = {journal},
title = {Ontology Based Knowledge Management System Design for Organic Farming},
author = {Ahmed, Muqeem and Fathima, Afrah and Islam, Mohammad and Arundhathi, Tunga and Khan, Amir and Gulzar, MD},
volume = {22},
number = {3},
year = {2026},
month = {Mar},
pages = {1060-1072},
doi = {10.3844/jcssp.2026.1060.1072},
url = {https://thescipub.com/abstract/jcssp.2026.1060.1072},
abstract = {In the current agricultural system, information is often gathered manually, and farmers make decisions based on their judgment. Occasionally, they seek advice from experts and extension officers. Numerous information systems have recently emerged, offering insights into organic farming practices. However, this information is dispersed across various contexts, formats, and media on the Internet, making it challenging to access. Utilizing ontology with a conceptual framework allows for the thorough and detailed formalization of any subject area. This research aims to gather, store, and supply organic farming information to current and prospective software developers interested in creating applications for farmers. It uses information extraction and development methods to create an ontology-based information extraction system for organic farming. The knowledge base was constructed using the Protégé editor. Meanwhile, Hermit was used to ensure the ontology's consistency by using reasoning techniques and to submit queries to verify their accuracy. These queries are formulated in description logic and evaluate the ontology's ability to answer farmer queries by presenting instances of competency questions from the Description Language query interface. The responses generated by the ontology were promising, indicating its effectiveness as a knowledge repository.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}