Ontologies for modeling and simulation: issues and approaches
WSC '04 Proceedings of the 36th conference on Winter simulation
Using ontologies for simulation modeling
Proceedings of the 38th conference on Winter simulation
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The translational challenge in biomedical research lies in the effective and efficient transfer of mechanistic knowledge from one biological context to another. Implicit in this process is the establishment of causality from correlation in the form of mechanistic hypotheses. Effectively addressing the translational challenge requires the use of automated methods, including the ability to computationally capture the dynamic aspect of putative hypotheses such that they can be evaluated in a high throughput fashion. Ontologies provide structure and organization to biomedical knowledge; converting these representations into executables/simulations is the next necessary step. Researchers need the ability to map their conceptual models into a model specification that can be transformed into an executable simulation program. We suggest this composition function can be expressed as a set of logical rules, which an intelligent computational agent, a Composing Agent (CompAgt), performs reasoning upon to develop a plan to achieve that composition. Presented herein is a description for a composition operation between biomedical and simulation ontologies that can be performed by a CompAgt to produce executable code for dynamic knowledge representation.