A recent publication from the DECIDE project published in Smart Agricultural Technology provides a focused assessment of how livestock disease surveillance can be improved through better data integration and the use of ontologies. With infectious diseases continuing to affect both terrestrial and aquatic livestock systems, the need for interoperable and scalable surveillance solutions is increasingly critical.
About the review
The article, authored by Saba Noor, Jeroen Degroote, Gerdien van Schaik, Bart Pardon, Céline Faverjon, Camille Delavenne and Miel Hostens, presents a systematic literature review following PRISMA 2020 guidelines, supported by a machine learning-based screening tool. Out of 286 screened records, 100 records were included, covering both ontology-based and alternative approaches to livestock disease surveillance.
Key findings
The study confirms that livestock health data remain highly fragmented. Although precision livestock farming generates large datasets, their use is limited by poor interoperability, data silos, security concerns and low farmer adoption. Ontologies offer a structured approach to integrating heterogeneous data across systems and species.
However, important limitations persist. Of 32 identified ontologies, only 15 are currently active, while many lack comprehensive disease coverage. Additional challenges include system complexity, maintenance requirements and insufficient domain representation, all of which reduce practical applicability.
Relevance for DECIDE
The publication highlights the contribution of initiatives such as DECIDE in addressing these gaps. Through open tools, training and collaborative approaches, DECIDE supports the development of more robust and interoperable surveillance systems, aligned with European priorities on animal health and food system resilience.
Questions for the community
The findings raise several important questions for researchers, policymakers and practitioners alike. How can interoperability between livestock data systems be effectively achieved in practice? What mechanisms are needed to ensure the long-term sustainability and maintenance of ontologies? How can farmer engagement and trust in digital tools be increased? And how can collaborative initiatives like DECIDE accelerate the transition towards integrated, ontology-based surveillance systems?
Addressing these questions will be essential to unlock the full potential of data-driven livestock health management and to ensure more resilient, sustainable and secure food systems in Europe and beyond.