Toward Semantic Explainable AI in Livestock: MoonCAB Enrichment for O-XAI to Sheep BCS Prediction

Nourelhouda Hammouda, Mariem Mahfoudh, Khouloud Boukadi

2025

Abstract

Body Condition Score (BCS) is a key metric for monitoring the health, productivity, and welfare of livestock, playing a crucial role in supporting farmers and experts in effective herd management. Despite advancements in BCS prediction for cows and goats, no computer vision-based methods exist for sheep due to their complex body features. This absence, coupled with the lack of interpretability in existing AI models, hinders real-world adoption in sheep farming. To address this, we propose the first interpretable AI framework for sheep BCS prediction leveraging ontology-based knowledge representation. In this paper, we enrich the ontology MoonCAB, which models livestock behavior in pasture systems, with BCS-related knowledge to prepare it for future integration into explainable AI (XAI) systems. Our methodology involves enhancing the “Herd” module of MoonCAB with domain-specific concepts and 200 SWRL rules to support logical inference. The enriched ontology is evaluated using Pellet, SPARQL, and the MoOnEV tool. As a result, MoonCAB now enables reasoning-based support for BCS-related decision-making in precision sheep farming, laying the groundwork for future developments in ontology-based explainable AI (O-XAI).

Paper Citation

in Harvard Style

Hammouda N., Mahfoudh M. and Boukadi K. (2025). Toward Semantic Explainable AI in Livestock: MoonCAB Enrichment for O-XAI to Sheep BCS Prediction. In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD; ISBN 978-989-758-769-6, SciTePress, pages 52-63. DOI: 10.5220/0013717500004000

in Bibtex Style

@conference{keod25,
author={Nourelhouda Hammouda and Mariem Mahfoudh and Khouloud Boukadi},
title={Toward Semantic Explainable AI in Livestock: MoonCAB Enrichment for O-XAI to Sheep BCS Prediction},
booktitle={Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD},
year={2025},
pages={52-63},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013717500004000},
isbn={978-989-758-769-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD
TI - Toward Semantic Explainable AI in Livestock: MoonCAB Enrichment for O-XAI to Sheep BCS Prediction
SN - 978-989-758-769-6
AU - Hammouda N.
AU - Mahfoudh M.
AU - Boukadi K.
PY - 2025
SP - 52
EP - 63
DO - 10.5220/0013717500004000
PB - SciTePress