An algorithm, implementation and execution ontology design pattern

This paper describes an ontology design pattern for modeling algorithms, their implementations and executions. This pattern is derived from the research results on data mining/machine learning ontologies, but is more generic. We argue that the proposed pattern will foster the development of standards in order to achieve a high level of interoperability among in silico scientific experiments. We describe the intent of the pattern, provide competency questions and the pattern formalization. We also present an example instantiation of the pattern in the machine learning domain.