Representing default knowledge in biomedical ontologies: application to the integration of anatomy and phenotype ontologies.
BACKGROUND
Current efforts within the biomedical ontology community focus on achieving interoperability between various biomedical ontologies that cover a range of diverse domains. Achieving this interoperability will contribute to the creation of a rich knowledge base that can be used for querying, as well as generating and testing novel hypotheses. The OBO Foundry principles, as applied to a number of biomedical ontologies, are designed to facilitate this interoperability. However, semantic extensions are required to meet the OBO Foundry interoperability goals. Inconsistencies may arise when ontologies of properties - mostly phenotype ontologies - are combined with ontologies taking a canonical view of a domain - such as many anatomical ontologies. Currently, there is no support for a correct and consistent integration of such ontologies.


RESULTS
We have developed a methodology for accurately representing canonical domain ontologies within the OBO Foundry. This is achieved by adding an extension to the semantics for relationships in the biomedical ontologies that allows for treating canonical information as default. Conclusions drawn from default knowledge may be revoked when additional information becomes available. We show how this extension can be used to achieve interoperability between ontologies, and further allows for the inclusion of more knowledge within them. We apply the formalism to ontologies of mouse anatomy and mammalian phenotypes in order to demonstrate the approach.


CONCLUSIONS
Biomedical ontologies require a new class of relations that can be used in conjunction with default knowledge, thereby extending those currently in use. The inclusion of default knowledge is necessary in order to ensure interoperability between ontologies.
Hoehndorf
Robert
R
Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany. hoehndorf@eva.mpg.de
Loebe
Frank
F
Kelso
Janet
J
Herre
Heinrich
H
D000465:Algorithms; D000715:Anatomy; D000818:Animals; D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D007254:Information Science; D019359:Knowledge; D009323:Natural Language Processing; D010641:Phenotype; D015203:Reproducibility of Results; D012660:Semantics; D012984:Software; D018875:Vocabulary, Controlled