Research Article
Cotton Plant Pests and Phenology Knowledge Management in Côte d’Ivoire Using Semantic Web Technologies
@INPROCEEDINGS{10.1007/978-3-031-51849-2_14, author={Kouaho N’Guessan Narcisse Tehia and Sadouanouan Malo and Appoh Kouam\^{e} and Malanno Kouakou and Kouadio Kra Norbert Bini and Ochou Germain Ochou}, title={Cotton Plant Pests and Phenology Knowledge Management in C\~{o}te d’Ivoire Using Semantic Web Technologies}, proceedings={Innovations and Interdisciplinary Solutions for Underserved Areas. 6th EAI International Conference, InterSol 2023, Flic en Flac, Mauritius, September 16-17, 2023, Proceedings}, proceedings_a={INTERSOL}, year={2024}, month={2}, keywords={Knowledge management Semantic MediaWiki Ontology Web platform SPARQL RDF}, doi={10.1007/978-3-031-51849-2_14} }- Kouaho N’Guessan Narcisse Tehia
Sadouanouan Malo
Appoh Kouamé
Malanno Kouakou
Kouadio Kra Norbert Bini
Ochou Germain Ochou
Year: 2024
Cotton Plant Pests and Phenology Knowledge Management in Côte d’Ivoire Using Semantic Web Technologies
INTERSOL
Springer
DOI: 10.1007/978-3-031-51849-2_14
Abstract
In this paper, we are interested in the management of knowledge on the dynamics of pests and the phenology of cotton plant. This issue is a serious concern for the cotton sector in Côte d’Ivoire. Indeed, enormous parasitic pressures cause crop losses that vary between 30% and 100% of the production potential. A phytosanitary surveillance strategy for cotton has therefore been put in place. It is in this context that an ontologically based decision support system has been proposed. This system includes a mobile application for data collection and an ontology-based semantic wiki for knowledge management. The mobile application is deployed, and an ontology dedicated to the phytosanitary surveillance of cotton plant has been proposed. This ontology should be used as a knowledge base for the semantic wiki. We present in this paper the implementation of this semantic wiki that we call SYSPARCOT-CI WikiS. This platform is the first of its kind in cotton cultivation, mainly in phytosanitary surveillance. It is based on Semantic MediaWiki. The data from this semantic wiki as well as the data from the mobile application will be used to populate the ontology and to enrich it. The construction approach of our semantic wiki platform is based onontologies for wikis. Using the ontology we built, we constructed a semantic web platform. Then, using a Python script, this ontology was imported into the semantic wiki.
