TY - JOUR T1 - Benchmarking Ontologies: Bigger or Better? A1 - Yao, Lixia A1 - Divoli, Anna A1 - Mayzus, Ilya A1 - Evans, James A. A1 - Rzhetsky, Andrey Y1 - 2011/01/13 N2 - Author Summary An ontology represents the concepts and their interrelation within a knowledge domain. Several ontologies have been developed in biomedicine, which provide standardized vocabularies to describe diseases, genes and gene products, physiological phenotypes, anatomical structures, and many other phenomena. Scientists use them to encode the results of complex experiments and observations and to perform integrative analysis to discover new knowledge. A remaining challenge in ontology development is how to evaluate an ontology's representation of knowledge within its scientific domain. Building on classic measures from information retrieval, we introduce a family of metrics including breadth and depth that capture the conceptual coverage and parsimony of an ontology. We test these measures using (1) four commonly used medical ontologies in relation to a corpus of medical documents and (2) seven popular English thesauri (ontologies of synonyms) with respect to text from medicine, news, and novels. Results demonstrate that both medical ontologies and English thesauri have a small overlap in concepts and relations. Our methods suggest efforts to tighten the fit between ontologies and biomedical knowledge. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 7 IS - 1 UR - https://doi.org/10.1371/journal.pcbi.1001055 SP - e1001055 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1001055 ER -