With the advent of Model-Driven Engineering (MDE) several model transformation approaches and languages have been developed in the previous 5 years. Most of these existing approaches are metamodel-based with metamodels representing both an abstract syntax of the corresponding modeling language and also a data structure for storing models. However, this implementation specific focus makes it difficult for modelers to develop model transformations, because metamodels do not necessarily define all language concepts explicitly which are available for notation purposes. Therefore, we propose a by-example approach for defining inter-model mappings representing semantic correspondences between concrete domain models, which is more user-friendly, then directly specifying model transformation rules or mappings based on the abstract syntax. The intermodel mappings between domain models can be used to generate model transformation rules, by-example, taking into account the already defined mapping between abstract and concrete syntax elements. With this approach the user's knowledge about the notation of the modeling language is sufficient for the definition of model transformations regarding semantic correspondences. Hence, no detailed knowledge about the metamodel and the model transformation language is required.

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.

Abstract. Seamless exchange of models among different modeling tools increasingly becomes a crucial prerequisite for the success of modeldriven engineering. Current best practices use model transformation languages to realize necessary mappings between concepts of the metamodels defining the modeling languages supported by different tools. Existing model transformation languages, however, lack appropriate abstraction mechanisms for resolving recurring kinds of structural heterogeneities one has to primarily cope with when creating such mappings. We propose a framework for building reusable mapping operators which allow the automatic transformation of models. For each mapping operator, the operational semantics is specified on basis of Colored Petri Nets, providing a uniform formalism not only for representing the transformation logic together with the metamodels and the models themselves, but also for executing the transformations, thus facilitating understanding and debugging. To demonstrate the applicability of our approach, we apply the proposed framework for defining a set of mapping operators which are intended to resolve typical structural heterogeneities occurring between the core concepts usually used to define metamodels.

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International audienceOntologies offer shared vocabularies that are key to agent cooperation and knowledge systems integration as well as fundamental to the Semantic Web. As the number of ontologies increases, so does the need for new tools and techniques to establish agreement between different knowledge representatuions. Six essays based on papers accepted for the First Workshop on Ontology Alignment and Visualization (OnAV 2008) exemplify some of the ways researchers are extending the state of the art in algorithms that can establish correspondences between different but related onologies