Achieving Semantic Interoperability between Physiology Models and Clinical Data

The practice and research of biomedicine generates considerable quantities of data and model resources (DMRs). The RICORDO effort works closely with modelling communities in the physiology and pharmacology domains to provide a semantic interoperability framework that addresses obstacles to biomedical DMR sharing. The RICORDO framework adopts a core set of community supported standard reference ontologies with which to effect, and reason over, modelling resource metadata. In some cases, knowledge in reference ontologies that is critical to particular interoperability objectives may be incomplete. The specific objective discussed in this paper focuses on the derivation of semantic interoperability between cardiovascular physiology models and related clinical data. In particular, the aim of this work is to semantically infer the anatomical relationship between variables in the Guyton circulatory model and data annotated with vascular disease terms from SNOMED-CT and the International Classification of Disease (ICD-10). The cardiovascular knowledgebase in the Foundational Model of Anatomy (FMA) was curated to provide a more extensive coverage of terms and relations referred to in Guyton model variables and related clinical data. A knowledge representation of cardiovascular connectivity was also developed with which to infer the topological features of the cardiovascular system exported from the curated knowledgebase. This approach allowed the calculation of semantic distance between physiology model variables and disease terms on the basis of their involvement with specific cardiovascular structures. The resulting methodology and associated extended knowledgebase allow the comparison of DMR metadata arising from annotations that conform to the RICORDO ontology standard. In particular, this approach quantifiably and semantically relates physiology and disease concepts annotating mathematical models and clinical data.