Support for User Involvement in Data Cleaning

Data cleaning and ETL processes are usually modeled as graphs of data transformations. The involvement of the users responsible for executing these graphs over real data is important to tune data transformations and to manually correct data items that cannot be treated automatically. In this paper, in order to better support the user involvement in data cleaning processes, we equip a data cleaning graph with data quality constraints to help users identifying the points of the graph and the records that need their attention and manual data repairs for representing the way users can provide the feedback required to manually clean some data items. We provide preliminary experimental results that show the significant gains obtained with the use of data cleaning graphs.