An ontology-driven framework for animal traceability

Abstract

Traceability systems are crucial for regulatory compliance and consumer trust in food supply integrity and animal protection. Animal traceability systems ensure food safety and disease outbreak control. However, the current systems lack interoperability and are badly integrated across multiple stakeholders. The non-interoperable animal traceability systems pose challenges for farmers and the government in tracking stray animals, diseases, feeding, vaccinations, and livestock export regulations. The main cattle identification and traceability system being used in Botswana is the non-interoperable Botswana Livestock Identification and Traceability System. The six stakeholders concentrate on cow but lack a single system for interoperability, integration, standardization, and domain understanding among them. This research proposes the development of an interoperable and ontology-driven animal traceability framework to solve the gap of poor interoperability in current frameworks for animal traceability, with Botswana as a case study. Limitations of current traceability frameworks were identified, and the components for the design and development of the proposed interoperability framework were generated using the mixed method design methodology - qualitative and quantitative research. Involving robust data analysis. Quantitative identified system gaps and patterns in traceability practices though descriptive statistics. Qualitative research carried out a thematic analysis using NVivo tool on stakeholder interviews and documents, for in-depth understanding of socio-technical aspects of traceability systems. Together the designs reinforced the validity and reliability of the findings. The analysis identified cattle, farmers, system, and records as the key concepts. 39% of Botswana participants find BAITS ineffective, making it the main challenge of animal traceability. An interoperable ontology-driven animal traceability framework is developed. In addition, a new and novel animal traceability ontology was developed using the METHONTOLOGY ontology development methodology, covering knowledge acquisition, specification, conceptualization, formalization, and evaluation. The process ensures a transparent and systematic ontology development of the animal traceability domain to model the key traceability components. The ontology was evaluated for quality based on consistency, clarity, adaptability, and coverage. The Ontometric evaluation tool was used to evaluate revealing a high level of inheritance richness 0.692308, relationship richness 0.678571, and average depth 0.9, indicating detailed knowledge ontology, strong class connections, and seamless data integration and exchange. The evaluation of reference and candidate ontologies revealed 66.67% of animal traceability ontology is more interoperable than animal health ontology at 33.33%. Altogether, results indicate that the framework achieved interoperability and standardization, producing seamless integrated systems. Overall, this study contributes both as a template that is methodological for agricultural research in semantic systems. Also, providing a foundation for adaptable solutions to support worldwide supply chain compliance and strategies in animal health. The ontology-driven framework is designed as a guiding principle for system developers, a blueprint to implement semantically correct integrated traceability. The ontology is developed to contribute semantic interoperability and can be integrated with data infrastructures already existing.