Título : Evaluation of ontology structural metrics based on public repository data |
Autor : Franco, Manuel Vivo, Juana María Quesada-Martínez, Manuel Duque-Ramos, Astrid Fernández-Breis, Jesualdo Tomás |
Editor : Oxford University Press |
Departamento: Departamentos de la UMH::Estadística, Matemáticas e Informática |
Fecha de publicación: 2019-02 |
URI : https://hdl.handle.net/11000/38781 |
Resumen :
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.
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Palabras clave/Materias: Biological ontologies Quantitative metrics Metrics comparison Data analysis |
Tipo de documento : info:eu-repo/semantics/article |
Derechos de acceso: info:eu-repo/semantics/openAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
DOI : 10.1093/bib/bbz009 |
Publicado en: Briefings in Bioinformatics, Vol. 21, Nº2 (2020) |
Aparece en las colecciones: Artículos - Estadística, Matemáticas e Informática
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