Evaluation of ontology structural metrics based on public repository data

• Published in: Briefings in bioinformatics Vol. 21; no. 2; pp. 473 - 485
• Main Authors: Franco, Manuel, Vivo, Juana María, Quesada-Martínez, Manuel, Duque-Ramos, Astrid, Fernández-Breis, Jesualdo Tomás
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 23.03.2020; Oxford Publishing Limited (England)
• Subjects: Clustering; Correlation analysis; Evaluation; Ontology; Repositories; Stability analysis; quantitative metrics; data analysis; biological ontologies; metrics comparison
• ISSN: 1467-5463; 1477-4054; 1477-4054
• DOI: 10.1093/bib/bbz009

Abstract The development and application of biological ontologies have increased significantly in recent years. These ontologies can be retrieved from different repositories, which do not provide much information about quality aspects of the ontologies. In the past years, some ontology structural metrics have been proposed, but their validity as measurement instrument has not been sufficiently studied to date. In this work, we evaluate a set of reproducible and objective ontology structural metrics. Given the lack of standard methods for this purpose, we have applied an evaluation method based on the stability and goodness of the classifications of ontologies produced by each metric on an ontology corpus. The evaluation has been done using ontology repositories as corpora. More concretely, we have used 119 ontologies from the OBO Foundry repository and 78 ontologies from AgroPortal. First, we study the correlations between the metrics. Second, we study whether the clusters for a given metric are stable and have a good structure. The results show that the existing correlations are not biasing the evaluation, there are no metrics generating unstable clusterings and all the metrics evaluated provide at least reasonable clustering structure. Furthermore, our work permits to review and suggest the most reliable ontology structural metrics in terms of stability and goodness of their classifications. Availability: http://sele.inf.um.es/ontology-metrics