Manipulation of models and mappings is a common task in the design and development of information systems. Research in Model Management aims at supporting these tasks by providing a set of operators to manipulate models and mappings. As a framework, GeRoMeSuite provides an environment to simplify the implementation of model management operators. GeRoMeSuite is based on the generic role based metamodel GeRoMe [10], which represents models from different modeling languages (such as XML Schema, OWL, SQL) in a generic way. Thereby, the management of models in a polymorphic fashion is enabled, i.e. the same operator implementations are used regardless of the original modeling language of the schemas. In addition to providing a framework for model management, GeRoMeSuite implements several fundamental operators such as Match, Merge, and Compose. 1.

Abstract. Schema mappings come in different flavors: simple correspondences are produced by schema matchers, intensional mappings are used for schema integration. However, the execution of mappings requires a formalization based on the extensional semantics of models. This problem is aggravated if multiple metamodels are involved. In this paper we present extensional mappings, that are based on second order tuple generating dependencies, between models in our Generic Role-based Metamodel GeRoMe. By using a generic metamodel, our mappings support data translation between heterogeneous metamodels. Our mapping representation provides grouping functionalities that allow for complete restructuring of data, which is necessary for handling nested data structures such as XML and object oriented models. Furthermore, we present an algorithm for mapping composition and optimization of the composition result. To verify the genericness, correctness, and composability of our approach we implemented a data translation tool and mapping export for several data manipulation languages. 1

Model Management aims at developing new technologies and mechanisms to support the integration, evolution and matching of models. Such tasks are to be performed by means of a set of operators which work on models and their elements. Furthermore, model management performs these operations generically, that is, without being restricted to a particular metamodel (e.g. the relational or XML Schema metamodel). In order to allow this, a generic metamodel must be used for model representation. Operators manipulate exclusively models described in that generic language. Consequently, models represented in concrete metamodels have to be imported into the generic metamodel and vice versa. In this paper we describe how we implemented rule based Import and Export operators between concrete metamodels and our generic role based metamodel GeRoMe. In addition, the same rule based approach can be used to implement one of the main model management operators, namely ModelGen, in a generic way. This operator is used to transform models using certain constructs into models using other modeling constructs.

In this article we present extensional mappings, that are based on second order tuple generating dependencies between models in our Generic Role-based Metamodel GeRoMe. Our mappings support data translation between heterogeneous models, such as XML Schemas, relational schemas, or OWL ontologies. The mapping language provides grouping functionalities that allow for complete restructuring of data, which is necessary for handling object oriented models and nested data structures such as XML. Furthermore, we present algorithms for mapping composition and optimization of the composition result. To verify the genericness, correctness, and composability of our approach we implemented a data translation tool and mapping export for several data manipulation languages. Furthermore, we address the question how generic schema mappings can be harnessed for answering queries against an integrated global schema.

Abstract. Schema matching is the task of automatically computing correspondences between schema elements. A multitude of schema matching approaches exists for various scenarios using syntactic, semantic, or instance information. The schema matching problem is aggravated by the fact that models to be matched are often represented in different modeling languages, e.g. OWL, XML Schema, or SQL DDL. Consequently, besides being able to match models in the same metamodel, a schema matching tool must be able to compute reasonable results when matching models in heterogeneous modeling languages. Therefore, we developed a matching component as a part of our model management system GeRoMeSuite which is based on our generic metamodel GeRoMe. As GeRoMe provides a unified representation of models, the matcher is able to match models represented in different languages with each other. In this paper, we will show in particular the results for matching XML Schemas with OWL ontologies as it is often required for the semantic annotation of existing XML data sources. GeRoMeSuite allows for flexible configuration of the matching system; various matching algorithms for element and structure level matching are provided and can be combined freely using different ways of aggregation and filtering in order to define new matching strategies. This makes the matcher highly configurable and extensible. We evaluated our system with several pairs of XML Schemas and OWL ontologies and compared the performance with results from other systems. The results are considerably better which shows that a matching system based on a generic metamodel is favorable for heterogeneous matching tasks. 1

Abstract. GeRoMeSuite is a generic model management system which provides several functions for managing complex data models, such as schema integration, definition and execution of schema mappings, model transformation, and matching. The system uses the generic metamodel GeRoMe for representing models, and because of this, it is able to deal with models in various modeling languages such as XML Schema, OWL, ER, and relational schemas. A component for schema matching and ontology alignment is also part of the system. We participated this year the first time in the OAEI contest in order to evaluate and compare the performance of our matcher component with other systems. Therefore, we focused our efforts on the ‘benchmark ’ track. 1 Presentation of the system Manipulation of models and mappings is a common task in the design and development of information systems. Research in Model Management aims at supporting these tasks by providing a set of operators to manipulate models and mappings. As a framework, GeRoMeSuite [4] provides an environment to simplify the implementation of

Abstract. Schema integration is the procedure to integrate several inter-related schemas to produce a unified schema, called the mediated schema. There are two major flavors of schema integration: data integration and view integration. The former deals with integrating multiple data sources to create a mediated query interface, while the latter aims at constructing a base schema, capable of supporting the source schemas as views. Our work builds upon previous approaches that address relational view integration using logical mapping constraints. Given a set of data dependencies over the source schemas as input, our approach produces a minimal information-preserving mediated schema with constraints, and it generates output mappings defining the source schemas as views. We extend previous approaches in several aspects. First, schema minimization is performed within a scope of Project-Join views that are information preserving and produce a smaller mediated schema than in existing work. Second, the input schema mapping language is expressive enough for not only query containment but also query equivalence. Third, source integrity constraints can be seamlessly incorporated into reasoning. Last but not least, we have evaluated our implementation over both real world data sets and a schema mapping benchmark. 1