@InProceedings{10.1007/978-3-031-43458-7_29,
author="Hamed, Naeima
and Rana, Omer
and Goossens, Beno{\^i}t
and Orozco-terWengel, Pablo
and Perera, Charith",
editor="Pesquita, Catia
and Skaf-Molli, Hala
and Efthymiou, Vasilis
and Kirrane, Sabrina
and Ngonga, Axel
and Collarana, Diego
and Cerqueira, Renato
and Alam, Mehwish
and Trojahn, Cassia
and Hertling, Sven",
title="FOO: An Upper-Level Ontology for the Forest Observatory",
booktitle="The Semantic Web: ESWC 2023 Satellite Events",
year="2023",
publisher="Springer Nature Switzerland",
address="Cham",
pages="154--158",
abstract="Wildlife and preservation research activities in the tropical forest of Sabah, Malaysia, can generate a wide variety of data. However, each research activity manages its data independently. Since these data are disparate, gaining unified access to them remains a challenge. We propose the Forest Observatory Ontology (FOO) as a basis for integrating different datasets. FOO comprises a novel upper-level ontology that integrates wildlife data generated by sensors. We used existing ontological resources from various domains (i.e., wildlife) to model FOO's concepts and establish their relationships. FOO was then populated with multiple semantically modelled datasets. FOO structure and utility are subsequently evaluated using specialised software and task-based methods. The evaluation results demonstrate that FOO can be used to answer complex use-case questions promptly and correctly.",
isbn="978-3-031-43458-7"
}