In the modern era, databases have been created spanning many domains. However, these databases do not contain general knowledge about their respective domains. For example, whereas a medical database could contain an entry for a patient with some medical disorder, it would not normally contain taxonomic information about medical disorders, known causal agents, symptoms, etc. Collections of this sort of general information are usually called knowledge bases and powerful tools have been developed for querying these collections in complex and flexible ways. The research described in this abstract aims to develop methodologies for merging existing databases with knowledge bases, so that the power and flexibility of knowledge base technology can be applied to existing collections of data.