Standard-based integration and semantic enrichment of clinical data originating from electronic medical records has shown to be critical to enable secondary use. To facilitate the utilization of semantic technologies on clinical data, we introduce a methodology to enable automated transformation of openEHR-based data to Web Ontology Language (OWL) individuals. To test the correctness of the implementation, de-identified data of 229 patients of the pediatric intensive care unit of Hannover Medical School has been transformed into 2.983.436 individuals. Querying of the resulting ontology for symptoms of the systemic inflammatory response syndrome (SIRS) yielded the same result set as a SQL query on an openEHR-based clinical data repository.