title: Measuring the evolution of ontology complexity: the gene ontology case study.
abstract: Ontologies support automatic sharing, combination and analysis of life sciences data. They undergo regular curation and enrichment. We studied the impact of an ontology evolution on its structural complexity. As a case study we used the sixty monthly releases between January 2008 and December 2012 of the Gene Ontology and its three independent branches, i.e. biological processes (BP), cellular components (CC) and molecular functions (MF). For each case, we measured complexity by computing metrics related to the size, the nodes connectivity and the hierarchical structure. The number of classes and relations increased monotonously for each branch, with different growth rates. BP and CC had similar connectivity, superior to that of MF. Connectivity increased monotonously for BP, decreased for CC and remained stable for MF, with a marked increase for the three branches in November and December 2012. Hierarchy-related measures showed that CC and MF had similar proportions of leaves, average depths and average heights. BP had a lower proportion of leaves, and a higher average depth and average height. For BP and MF, the late 2012 increase of connectivity resulted in an increase of the average depth and average height and a decrease of the proportion of leaves, indicating that a major enrichment effort of the intermediate-level hierarchy occurred. The variation of the number of classes and relations in an ontology does not provide enough information about the evolution of its complexity. However, connectivity and hierarchy-related metrics revealed different patterns of values as well as of evolution for the three branches of the Gene Ontology. CC was similar to BP in terms of connectivity, and similar to MF in terms of hierarchy. Overall, BP complexity increased, CC was refined with the addition of leaves providing a finer level of annotations but decreasing slightly its complexity, and MF complexity remained stable.
authors.affiliation: Université de Rennes, Rennes, France ; Institut de Recherche en Informatique et Systèmes Aléatoires, Rennes, France.
authors.forename: Olivier
authors.initials: O
authors.lastname: Dameron
authors.forename: Charles
authors.initials: C
authors.lastname: Bettembourg
authors.forename: Nolwenn
authors.initials: N
authors.lastname: Le Meur
mesh_terms: D019295:Computational Biology / Q000266:history*; D063990:Gene Ontology / Q000706:statistics & numerical data / Q000639:trends*; D049674:History, 21st Century; D006801:Humans; D013997:Time Factors; D018875:Vocabulary, Controlled / Q000266:history*