@inproceedings2010, Title = {Interchangeable consistency constraints for public health care systems}, Year = {2010}, Month = {03}, Editor = {Sung Y. Shin and Sascha Ossowski and Michael Schumacher and Mathew J. Palakal and Chih-Cheng Hung}, Isbn = {978-1-60558-639-7}, Booktitle = {Proceedings of the 2010 ACM Symposium on Applied Computing (SAC)}, Organization = {ACM}, type = {inproceedings}, note = {Severe data quality problems exist in most public health care systems and inconsistent data sets often occur. Consistency constraints can be used to de ne valid and invalid data. Existing solutions of such constraints like rule systems are often diffc}, Abstract = {Severe data quality problems exist in most public health care systems and inconsistent data sets often occur. Consistency constraints can be used to de ne valid and invalid data. Existing solutions of such constraints like rule systems are often diffcult to maintain, not human-readable, and of a bad quality like containing contradictory rules. With In- DaQu we present an approach that allows domain experts to easily create and maintain consistency constraints using an introduced domain-speci c language. These constraints are being stored in an ontology, which allows for an automated inconsistency detection in the de ned rules themselves. We identi ed several scenarios in which consistency constraints can be interchanged and exchanged between di erent participants. The approach has been successfully evaluated in the cancer registry of Lower Saxony.} @COMMENTBibtex file generated on