Abstract. The use of different modeling languages in software development makes their integration a must. Most existing integration approaches are metamodel-based with these metamodels representing both an abstract syntax of the corresponding modeling language and also a data structure for storing models. This implementation specific focus, however, does not make explicit certain language concepts, which can complicate integration tasks. Hence, we propose a process which semi-automatically lifts metamodels into ontologies by making implicit concepts in the metamodel explicit in the ontology. Thus, a shift of focus from the implementation of a certain modeling language towards the explicit reification of the concepts covered by this language is made. This allows matching on a solely conceptual level, which helps to achieve better results in terms of mappings that can in turn be a basis for deriving implementation specific transformation code.

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With the rise of model-driven software development, more and more development tasks are being performed on models. Seamless exchange of models among different modeling tools increasingly becomes a crucial prerequisite for effective software development processes. Due to lack of interoperability, however, it is often difficult to use tools in combination, thus the potential of model-driven software development cannot be fully utilized.To tackle this problem, we propose ModelCVS, a system aiming at model-based tool integration. ModelCVS enables transparent transformation of models between different tools' languages and exchange formats, as well as versioning exploiting the rich syntax and semantics of models, thus going beyond existing low-level model transformation approaches. For this, ModelCVS utilizes semantic technologies in terms of ontologies and supports different integration patterns at the metamodel level. To foster reuse, a knowledge base captures essential information relevant for tool integration.