Normalizing Heterogeneous Service Description Models with Generated QVT Transformations

Service Oriented Architectures (SOAs) enable the reuse and substitution of software services to develop highly flexible software systems. To benefit from the growing plethora of available services, sophisticated service discovery approaches are needed that bring service requests and offers together. Such approaches rely on rich service descriptions, which specify also the behavior of provided/requested services, e.g., by pre- and postconditions of operations. As a base for the specification a data schema is used, which specifies the used data types and their relations. However, data schemas are typically heterogeneous wrt. their structure and terminology, since they are created individually in their diverse application contexts. As a consequence the behavioral models that are typed over the heterogeneous data schemas, cannot be compared directly. In this paper, we present an holistic approach to normalize rich service description models to enable behavior-aware service discovery. The approach consists of a matching algorithm that helps to resolve structural and terminological heterogeneity in data schemas by exploiting domain-specific background ontologies. The resulting data schema mappings are represented in terms of Query View Transformation (QVT) relations that even reflect complex n:m correspondences. By executing the transformation, behavioral models are automatically normalized, which is a prerequisite for a behavior-aware operation matching.