Matching biodiversity and ecology ontologies: challenges and evaluation results. (2020)

• Record Type: Journal Article
• Authors: Karam, Naouel; Khiat, Abderrahmane; Algergawy, Alsayed; Sattler, Melanie; Weiland, Claus; Schmidt, Marco
• Is Part Of: Knowledge engineering review. Volume 35(2020)
• Publication Date: 2020
• Subjects: Expert systems (Computer science) -- Periodicals; 006.33
• DOI: 10.1017/S0269888920000132
• Languages: English
• ISSNs: 0269-8889

Abstract

Abstract: Biodiversity research studies the variability and diversity of organisms, including variability within and between species with particular focus on the functional diversity of traits and their relationship to environment. Managing biodiversity data implies dealing with its heterogeneous nature using semantics and tailored ontologies. These are themselves differently conceived, and combining them in semantically enabled applications necessitates an effective alignment between their concepts. This paper describes the ontology matching of biodiversity- and ecology-related ontologies. We illustrate diverse challenges introduced by this kind of ontologies to ontology matching in general. Real use cases requiring pairwise alignments between environment and trait ontologies are introduced. We describe our experience creating a new track at the Ontology Alignment Evaluation Initiative designed for this specific domain and report on the results obtained by state-of-the-art participating systems. The biodiversity and ecology use case turns out to be a strong one for ontology matching, introducing new interesting challenges. Even if most of the matching systems perform relatively well in the proposed matching tasks, there is still room for improvement. We highlight possible directions in that matter and elaborate on our plan to further progress with the track.