A semantics-preserving exchange of information between two software applications requires mappings between logically equivalent concepts in the ontology of each application. The challenge of semantic integration is therefore equivalent to the problem of generating such mappings, determining that they are correct, and providing a vehicle for executing the mappings, thus translating terms from one ontology into another. Current approaches to semantic integration do not fully exploit the model-theoretic structures underlying ontologies. They are typically based on the taxonomic structure of the terminology (, ) or heuristics-based comparisons of the symbols of the terminology ([1, 8]). These approaches are well-suited to working with many ontologies currently under development, most of which define a terminology with minimal formal grounding and a set of possible models which does not contain a rich set of features and properties. However, automated and correct approaches to semantic integration will require ontologies with a deeper formal grounding so that strong decisions may be made by automated process in comparing ontologies for integration. This article presents an approach to this goal, by presenting techniques based on the development of strong ontologies with terminologies grounded in properties of the underlying possible models. With these as inputs, semi-automated and automated components may be used to create mapping between ontologies and perform translations.