International Journal of Education and Management Engineering (IJEME)
IJEME Vol. 16, No. 3, 8 Jun. 2026
Cover page and Table of Contents: PDF (size: 1052KB)
ONTOGRAZING: A Semantic Monitoring and Decision-Support Framework for Sustainable Grazing Management
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Author(s)
Ngazia Balama
1
Gazissou Balama
2,3
Isaac Touza
2,3,*
Daouda Hassana Daouda
1
Dayang Paul
1,3
Index Terms
Grazing Ontology, Semantic Web, OWL, Sustainable Agriculture, Iot, Pasture Management, Knowledge Representation, Agro-Pastoral Systems
Abstract
Sustainable grazing management requires balancing livestock productivity with ecosystem preservation, yet existing monitoring systems integrate heterogeneous data from IoT sensors, satellite imagery, and field surveys without a unified semantic layer, limiting holistic decision support. This paper proposes ONTOGRAZING, an ontology-based monitoring architecture for sustainable grazing management. Using the Uschold and King ontology engineering framework, domain knowledge was collected through surveys involving 23 livestock farmers and 4 agro-pastoral institutions in Cameroon, complemented by a systematic literature review. Seven core concepts and fourteen semantic relationships were modeled in OWL using Protégé. A five-module monitoring architecture composed of Query Reformulator, Data Integrator, Source Monitoring, Alert, and Storage modules was designed around the ontology. ONTOGRAZING was evaluated using the HermiT 1.4.3.456 reasoner and SPARQL queries. The ontology contains 47 classes, 14 object properties, and 9 data properties, and passed all consistency checks. Comparative analysis demonstrates that ONTOGRAZING is the first ontology to jointly cover forage management, dietary preferences, pasture composition, ecological–economic trade-offs, and land-use regulations. These results highlight the potential of ontology-based integration to improve interoperability and semantic decision support in agro-pastoral systems, while future work will focus on full prototype implementation and integration with real-world IoT platforms and agricultural databa.
Cite This Paper
Ngazia Balama, Gazissou Balama, Isaac Touza, Daouda Hassana Daouda, Dayang Paul, "ONTOGRAZING: A Semantic Monitoring and Decision-Support Framework for Sustainable Grazing Management", International Journal of Education and Management Engineering (IJEME), Vol.16, No.3, pp. 1-14, 2026. DOI:10.5815/ijeme.2026.03.01
Reference
[1]N. Markov, S. Stoycheva, M. Hristov, and L. Mondeshka, "Digital management of technological processes in cattle farms: a review," Journal of Central European Agriculture, vol. 23, no. 3, pp. 486–495, 2022. https://doi.org/10.5513/JCEA01/23.3.3543
[2]G. Barber and T. E. Ochsner, "Using soil moisture sensors to improve agricultural water management in Southwest Oklahoma," in ASA, CSSA, SSSA International Annual Meeting, 2021. https://doi.org/10.1002/csan.20353
[3]M. López-Vicente et al., "Role of cultivars and grass in the stability of soil moisture and temperature in an organic vineyard," Geoderma Regional, vol. 33, p. e00631, 2023. https://doi.org/10.1016/j.geodrs.2023.e00631
[4]A. Clark, "Small unmanned aerial systems comparative analysis for the application to coastal erosion monitoring," GeoResJ, vol. 13, pp. 175–185, 2017.https://doi.org/10.1016/j.grj.2017.05.001
[5]Q.-R. Wang, "Application of small unmanned aerial vehicles to improving vegetable crop management," 2020, pp. 98–100. https://www.cabidigitallibrary.org/doi/pdf/10.5555/20220227222
[6]R. Kappes et al., "Evaluation of an electronic system for monitoring dairy cow rumination in a grazing-based system," Tropical Animal Health and Production, vol. 53, no. 3, p. 379, 2021. https://doi.org/10.1007/s11250-021-02833-w
[7]A. Hlimi et al., "Application of precision technologies to characterise animal behaviour: a review," Animals, vol. 14, no. 3, p. 416, 2024. https://doi.org/10.3390/ani14030416
[8]J. Marston and L. Burwood-Taylor, "Bayer, Microsoft formalize and launch cloud-based data manager for agriculture," AgFunder News, 2023. https://agfundernews.com/bayer-microsoft-formalize-and-launch-cloud-based-data-manager
[9]L. Leeuw, Indiana Farmers' Level of Adoption and Perceptions of Mobile Applications as Agricultural Management Tools. Diss., Purdue University, 2019. https://doi.org/10.25394/PGS.8044295.v1
[10]L. Irvine and L. Turner, "Pasture measurement data improves timeliness and confidence in grazing management decisions," in Proc. 8th Australasian Dairy Science Symposium, 2018, pp. 12–17. https://static.sched.com/hosted_files/adss2018/c9/87798%20Irvine%20Turner%20ADSS%20Paper%20UPDATED.pdf
[11]I. Devi et al., "Application of artificial intelligence and IoT technologies in agriculture and animal farming," Indian Farming, vol. 72, no. 10, pp. 22–25, 2022. https://epubs.icar.org.in/index.php/IndFarm/article/view/129642
[12]A. Laporte, "Investigation of the functionality of electronic data capture and management systems for use in a modern animal health industry," 2024. https://krex.k-state.edu/items/8cf6e587-bd37-47a9-a053-aabbc5afb30a
[13]A. Todirascu, L. Romary, and D. Bekhouche, "Extraction d'information à base d'ontologies dans une application de veille," in 5ème TIA'2003, 2003, pp. 205–208. https://inria.hal.science/inria-00107715v1/document
[14]D. Maynard et al., "Ontology-based information extraction for market monitoring and technology watch," in ESWC Workshop, 2005. https://kmi.open.ac.uk/events/usersweb/papers/03_maynard_final.pdf
[15]T. D. Cao, "Exploitation du web sémantique pour la veille technologique," Ph.D. thesis, Université Nice Sophia Antipolis, 2006. https://theses.hal.science/tel-00311767/document
[16]A. Hodgson, H. Arman, and N. N. Z. Gindy, "An intelligent technology watch function for the high technology enterprise," International Journal of Industrial and Systems Engineering, vol. 3, no. 1, pp. 38–52, 2008. https://doi.org/10.1504/IJISE.2008.015913
[17]J. P. C. Verhoosel and J. Spek, "Applying ontologies in the dairy farming domain for big data analysis," in Proc. SR+SWIT@ISWC, 2016, pp. 91–100. https://ceur-ws.org/Vol-1783/paper-09.pdf
[18]S. L. Santamaria et al., "Developing the Animals in Context Ontology," in Proc. ICBO, 2012. https://www.researchgate.net/publication/266589978_Developing_the_Animals_in_Context_Ontology
[19]P.-Y. Le Bail, J. Bugeon, and L. Joret, "Projet Aquaexcel–ATOL," presented at Aquaexcel Kickoff Meeting, Montpellier, France, Apr. 2011. https://hal.inrae.fr/hal-02805009
[20]M.-C. Salaun et al., "Un outil au service de la standardisation des bases de données: les ontologies ATOL/EOL," Cahier des Techniques de l'INRA, no. 93, pp. 1–7, 2018. https://hal.inrae.fr/hal-02626650v1/document
[21]J. Yon et al., "Ontologie ATOL: amélioration de l'outil par l'intégration des caractères de santé," in Journées JAS Phase, 2018. https://hal.inrae.fr/hal-01768063
[22]R. Neches et al., "Enabling technology for knowledge sharing," AI Magazine, vol. 12, no. 3, p. 36, 1991. https://doi.org/10.1609/aimag.v12i3.902
[23]T. R. Gruber, "Toward principles for the design of ontologies used for knowledge sharing?" International Journal of Human-Computer Studies, vol. 43, no. 5–6, pp. 907–928, 1995. https://doi.org/10.1006/ijhc.1995.1081
[24]N. Guarino and P. Giaretta, "Ontologies and knowledge bases: towards a terminological clarification," in Towards Very Large Knowledge Bases, IOS Press, 1995, pp. 25–32. https://www.loa-cnr.it/Papers/KBKS95.pdf
[25]B. Swartout et al., "Toward distributed use of large-scale ontologies," in Proc. 10th Workshop on Knowledge Acquisition, 1996. https://www.researchgate.net/publication/243619379_Toward_Distributed_Use_of_Large-Scale_Ontologies_t
[26]W. N. Borst, "Construction of engineering ontologies for knowledge sharing and reuse," Ph.D. thesis, University of Twente, 1997. https://doi.org/10.3990/1.9789036509886
[27]M. Uschold and M. King, Towards a Methodology for Building Ontologies. Edinburgh: AIAI, 1995. https://www.aiai.ed.ac.uk/publications/documents/1995/95-ont-ijcai95-ont-method.pdf
[28]F. Gandon, "Distributed artificial intelligence and knowledge management: ontologies and multi-agent systems," Ph.D. thesis, Université Nice Sophia Antipolis, 2002. https://www.researchgate.net/publication/200637823_Distributed_Artificial_Intelligence_And_Knowledge_Management_Ontologies_
And_Multi-Agent_Systems_For_A_Corporate_Semantic_Web
[29]M. Fernandez-López et al., "METHONTOLOGY: from ontological art towards ontological engineering," in Proc. AAAI Spring Symposium, 1997. https://oa.upm.es/5484/1/METHONTOLOGY_.pdf
[30]A. Hamdi, Ontologie de domaine pour un web sémantique destiné au e-learning. Mémoire de master, Université Mouloud Mammeri de Tizi-Ouzou, 2011. Available: https://www.ummto.dz/dspace/bitstream/handle/ummto/12484/HamdiAhmed.pdf
[31]MU W, LIU T, MIAO Z, et al. Research progress on knowledge graph technology and its application in agriculture. Transactions of the Chinese Society of Agricultural Engineering, 2023, 39(16): 1-12. https://doi.org/10.11975/j.issn.1002-6819.202210028
[32]Maria Bermudez-Edo, Tarek Elsaleh, Payam Barnaghi, and Kerry Taylor. 2017. IoT-Lite: a lightweight semantic model for the internet of things and its use with dynamic semantics. Personal Ubiquitous Comput. 21, 3 (June 2017), 475–487. https://doi.org/10.1007/s00779-017-1010-8
[33]I. Subirats-Coll, K. Kolshus, A. Turbati, A. Stellato, E. Mietzsch, D. Martini, and M. Zeng, “AGROVOC: The linked data concept hub for food and agriculture,” Computers and Electronics in Agriculture, vol. 196, p. 105965, 2022. https://doi.org/10.1016/j.compag.2020.105965
[34]R. Grati, N. Fattouch, and K. Boukadi, “Ontologies for Smart Agriculture: A Path Toward Explainable AI – A Systematic Literature Review,” IEEE Access, 2024. https://doi.org/10.1109/ACCESS.2025.3563202