BART (Benchmarking Algorithms for data Repairing and Translation) is an error-generation tool for data cleaning applications. Its purpose is to introduce errors into clean databases for the purpose of benchmarking data-repairing algorithms. It provides users with the highest possible level of control over the error-generation process, and at the same time scales nicely to large databases. This is far from trivial, since, as we show in our technical papers, the error-generation problem is surprisingly challenging, and in fact, NP-complete. To scale to millions of tuples, the system relies on several non-trivial optimizations, including a new symmetry property of data quality constraints.

Additional material about the project (papers and example datasets) can be found at the following address: http://db.unibas.it/projects/bart/

Execute script ./run <egtask.xml>, for example ./run.sh misc/resources/employees/employees-dbms-2k-egtask.xml

An EGTask is specified in an .xml file (here a template), with the following sections:

#####1. Database configuration ##### Is used to specify the JDBC parameters to access the DBMS. PostgreSQL and H2 DBMS are supported. Data can be automatically loaded into the database from XML and CSV files.

#####2. Dependencies specification #####

#####3. Task configuration #####

• printLog: (default = false)
• recreateDBOnStart: (default = false) To load DB every time on start
• applyCellChanges: (default = false) To apply cell changes
• cloneTargetSchema: (default = true) To apply cell changes on a copy of the original target
• useDeltaDBForChanges: (default = true) To use an optimized strategy for updates
• checkChanges: (default = false) To check, at the end of the process, if changes are detectable
• generateAllChanges: To generate all possible changes (default = false) - slow, only for toy examples
• avoidInteractions: Avoid interactions among changes. (default = true)
• errorPercentages: Error percentages for dependencies and comparisons. All percentages are wrt table sizes (# tuples)

How to evaluate a data-cleaning tool

1. In NetBeans, File -> Open projects... and select the project folder Bart_Engine
2. Execute ant target task gfp, either using command-line ant gfp, or using NetBeans (in the projects windows, right click on build.xml -> Run Target -> Other Targets -> gfp)