Ontology-Driven Smart Agriculture Framework: Ontology Modules, Rule Set, and Evaluation Scenarios

This repository provides the ontology modules, rule set, and supporting artifacts used in the study “Ontology-Driven AI Framework for Interoperable Smart Agriculture Systems.” The framework integrates heterogeneous agricultural inputs (IoT sensor observations, weather events, and farmer reports) into a semantic knowledge graph and derives agronomic recommendations using ontology-based reasoning and SWRL rules. The repository includes a modular ontology pack designed to support semantic interoperability and explainable decision support in smart agriculture environments. Repository Contents agri-core.owl – Core ontology defining agricultural entities such as crop plots, advisory actions, and recommendation structures. agri-sensor.owl – Ontology module representing sensor devices and observations aligned with semantic sensor modeling patterns. agri-weather.owl – Ontology module describing weather events and forecasts used for reasoning about environmental conditions. rules.swrl – A set of SWRL rules implementing agricultural decision logic (e.g., irrigation suppression after rainfall, irrigation triggering under low soil moisture, fertilization recommendation, forecast-based warnings, and conflict detection between farmer reports and sensor data). README.md – Documentation explaining how to load the ontologies, run reasoning, and reproduce inference results. Usage The ontology modules can be loaded into Protégé and executed using a description logic reasoner (e.g., Pellet or HermiT). After loading the SWRL rule set, the reasoner derives new knowledge graph assertions representing agronomic advisories and explanation traces. Purpose These artifacts enable reproducibility of the reasoning experiments reported in the associated research paper, including scenario-based validation and evaluation of explainability and safety constraints. License Specify the license you choose for the ontology artifacts (e.g., CC BY 4.0).