FOO: An Upper-Level Ontology for the Forest Observatory
Naeima Hamed, OMER F. RANA, Benoît Goossens, Pablo Orozco‐terWengel, Charith Perera · Lecture notes in computer science · 2023
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.