Abstract—There is an increase in the number of biomedical ontologies on the semantic web. Therefore, it is important to evaluate their complexity to promote their sharing and reuse in the biomedical domain. This study analyses and discusses the advanced complexity features of the biomedical ontologies stored in the BioPortal repository. A set of 100 biomedical ontologies from the BioPortal repository was collected. Thereafter, the collected ontologies are assigned to the analysis process to compute their advanced complexity metrics including the: size of the vocabulary, entropy of ontology graphs, the average number of paths per class, the tree impurity, class richness, percentage of part-of relations in the total number of relations, and many more. The results show that the biomedical ontologies studied are highly complex; this finding is evidenced by the analysis of their size of the vocabulary, average number of paths and entropy of ontology graph. However, it was interesting to learn that the structure of these ontologies favour their easy reuse and maintenance; these findings were reached through the analysis of the tree impurity, class and relationship richness of these ontologies.

Index Terms—Biomedical ontology, BioPortal, complexity of ontology, primitive ontology metrics, advanced complexity metrics.

Yannick Kazela Kazadi is with Departement of ICT, Vaal University of Technology, Private Bag X021, Andries Potgieter Blvd Vanderbijlpark, South Africa (email: yan.kazela@gmail.com).
Jean Vincent Fonou-Dombeu is with Department of Software Studies, Vaal University of Technology, Private Bag X021, Andries Potgieter Blvd.

Cite: Yannick Kazela Kazadi, Jean Vincent Fonou-Dombeu, "Analysis of Advanced Complexity Metrics of Biomedical Ontologies in the Bioportal Repository," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 7, no. 1, pp. 20-32, 2017.