Leveraging Ontology-Based Knowledge Management for Improved Data Quality and Enhanced Trade Compliance in Livestock Traceability Systems in Botswana
The problem addressed by this research is the struggle of Botswana’s livestock sector to implement effective animal traceability systems due to limited interoperability, inadequate data integration, reliance on open grazing systems, and systemic challenges like high mortality, theft, and disease outbreaks. These challenges collectively undermine animal traceability system competitiveness and compliance with international trade standards.
The paper addresses the problem by developing the Animal Traceability Ontology (ATO), standardizing data representation, and enabling seamless data sharing among stakeholders in Botswana’s livestock industry. This ontology improves interoperability, real-time data integration, and trade compliance, ultimately enhancing disease management and compliance with international trade standards.
The paper employed a mixed-methods research design, combining qualitative data collection through interviews and focus groups with stakeholders (such as farmers, veterinarians, and officials) and quantitative data through structured questionnaires. The ontology was developed using METHONTOLOGY, a widely adopted approach for ontology creation, and was evaluated using tools such as Protégé, Apache Jena Fuseki, and the Pellet reasoner. The research sample included key stakeholders in Botswana’s livestock industry, including farmers, veterinary officers, and representatives from the Botswana Meat Commission.
This research developed the ATO to enhance data quality and interoperability in livestock traceability systems. The ATO’s practical implications include fostering stakeholder collaboration, supporting small-scale farmers, enabling real-time disease management, and driving sustainable livestock practices. It addresses data heterogeneity and limited integration, providing a scalable framework for decision-making and compliance with international trade standards and offering a practical model to improve traceability across diverse systems.
The evaluation of the ATO assessed its structural, usability, and functional aspects, demonstrating its logical adequacy, stakeholder relevance, and performance efficiency. A comparative analysis with the Animal Health Ontology (AHO) revealed the ATO’s superior inheritance richness, relationship diversity, and tailored design for precise traceability applications, ensuring enhanced data integration, semantic clarity, and practical functionality for animal traceability systems. The ATO was, therefore, found to be a robust solution to Botswana’s livestock traceability challenges. The ATO has the potential to enhance Botswana’s livestock traceability by improving data quality, interoperability, real-time processing, and stakeholder collaboration, offering scalable tools for disease management, trade compliance, and sustainable livestock management.
Farmers should adopt affordable, user-friendly tools like mobile apps or compatible devices to streamline data entry and tracking. Regulatory agencies should promote training, ensure compliance with traceability standards, and provide subsidies for small-scale farmers. Collaboration among stakeholders will enhance system usability, real-time updates, and alignment with international trade standards.
The paper recommends that researchers leverage METHONTOLOGY for systematic ontology development, use tools like Protégé for evaluation, apply the ATO framework (or similar frameworks) to improve interoperability in other sectors, investigate its role in compliance and disease management, and examine its real-time data integration capabilities.
The ATO has the potential to positively impact farmers by streamlining livestock management, enabling efficient disease monitoring, reducing mortality rates, and boosting productivity and economic stability. For regulatory agencies, it ensures adherence to international trade standards, facilitates global market access, enhances public health, strengthens food safety, and bolsters national food security. Additionally, the ATO fosters collaboration and seamless data sharing among veterinarians, governmental and parastatal organizations (e.g., the BMC), and law enforcement, enhancing disease management, expanding market opportunities, and mitigating livestock theft.
Future research should explore the scalability of ATO (or similar ontologies), integrate advanced technologies like blockchain and IoT, develop simplified versions for resource-limited settings, expand research on real-time data analytics, and collaborate with industry stakeholders for practical alignment.
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