Currently, knowledge from biological research is stored in hundreds of databases, counting only public accessible ones. Finding specific data in these is a challenging task which can be supported by ontologies describing them. The maintenance of a corresponding ontology is time consuming manual work, because research database schemas change rapidly. Our project will reduce the work by automating tasks, like a generation process and applying schema changes to the corresponding ontology. We call the proposed method coevolution, because database schema and ontology are allowed to evolve independently without ever losing their connection to each other. Our method consists of initial ontology generation, manual annotation and change propagation steps.
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