Database systems allow to model information in a well-structured manner. Unfortunately, many databases cope with quality problems. A significant problem is the existence of coreferent data, which means that the same real world entity is described multiple times within one database. Due to errors, inaccuracies and a lack of standardization, coreferent data are not bound to be equal, which makes the finding of coreferent data a challenging topic. In this project it is studied how metadata can help to extract semantic knowledge which can be used to improve the detection of coreferent database objects.