Archetype-based semantic mediation: Incremental provisioning of data services

Modern organizations need to exploit the information stored in heterogeneous and interrelated data sources, but often have no means to integrate them in a principled fashion. This general database research challenge is particularly relevant in distributed e-Science. Specifically, biomed-ical research generates a vast amount of heterogeneous data, which exceeds the current technological capacity to exploit it efficiently. Typically, service-oriented architectures are used in this context to define a unified view over all sources to be integrated. This unified schema needs to be mapped onto the underlying data sources, often including also semantic annotations. This approach suffers from high complexity and setup costs. In this paper we propose a novel application of semantic and mediation technologies, which leads to an incremental and on-demand definition of data mediation services. The so-called archetypes provide the context and semantics needed to setup such services, which significantly simplify their definition.