In this project, we investigate how integrity constraints can be used in data cleaning. In particular, we investigate:

- a balance between expressivity of constraints and complexity of the fundamental algorithms (e.g., implication)

- the repair problem: how to turn inconsistent (dirty) data into consistent (clean) data in a cost-optimal manner

- the role of cost models in the generation of explainable consistent data