FOO: An upper-level ontology for the Forest Observatory

Hamed, Naeima, Rana, Omer ORCID: https://orcid.org/0000-0003-3597-2646, Goossens, Benoit ORCID: https://orcid.org/0000-0003-2360-4643 and Orozco Ter Wengel, Pablo ORCID: https://orcid.org/0000-0002-7951-4148 2023. FOO: An upper-level ontology for the Forest Observatory. Presented at: The Semantic Web 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece., 28 May – 1 June 2023.

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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.

Item Type:	Conference or Workshop Item (Poster)
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Date of First Compliant Deposit:	8 September 2023
Date of Acceptance:	13 April 2023
Last Modified:	05 Dec 2023 15:44
URI:	https://orca.cardiff.ac.uk/id/eprint/162349

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