@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 healthcare systems and inconsistent data sets often occur. Consistencyconstraints can be used to de ne valid and invaliddata. Existing solutions of such constraints like rule systemsare often diffc},Abstract = {Severe data quality problems exist in most public healthcare systems and inconsistent data sets often occur. Consistencyconstraints can be used to de ne valid and invaliddata. Existing solutions of such constraints like rule systemsare often diffcult to maintain, not human-readable, and ofa bad quality like containing contradictory rules. With In-DaQu we present an approach that allows domain experts toeasily create and maintain consistency constraints using anintroduced domain-speci c language. These constraints arebeing stored in an ontology, which allows for an automatedinconsistency detection in the de ned rules themselves. Weidenti ed several scenarios in which consistency constraintscan be interchanged and exchanged between di erent participants.The approach has been successfully evaluated inthe cancer registry of Lower Saxony.} @COMMENTBibtex file generated on