Maintaining state constraints in relational databases: a proof theoretic basis
Journal of the ACM (JACM)
A product perspective on total data quality management
Communications of the ACM
A general treatment of dynamic integrity constraints
Data & Knowledge Engineering
Dynamic constraints and database evolution
PODS '83 Proceedings of the 2nd ACM SIGACT-SIGMOD symposium on Principles of database systems
Data Quality Requirements Analysis and Modeling
Proceedings of the Ninth International Conference on Data Engineering
Incorporating business requirements and constraints in database conceptual models
APCCM '04 Proceedings of the first Asian-Pacific conference on Conceptual modelling - Volume 31
Beyond accuracy: what data quality means to data consumers
Journal of Management Information Systems
A Lifecycle Approach towards Business Rules Management
HICSS '08 Proceedings of the Proceedings of the 41st Annual Hawaii International Conference on System Sciences
ER '07 Tutorials, posters, panels and industrial contributions at the 26th international conference on Conceptual modeling - Volume 83
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Many researchers and practitioners have been attracted to improve data quality due to its monumental importance as a key success factor. Mathematical and statistical models have been deployed to information systems to introduce constrain and transaction based mechanisms to prevent data quality related problems. Entire management of the process and roles involved in data generation has also been scrutinized. Vast amount of knowledge base has been progressed in this area; however, most of the approaches are limited from practical perspective. System development process incorporating quality modelling is rarely integrated. Quality related meta data is absent from most information system. Neither process mapping nor data modelling provides sufficient provision to measure quality or certification of data in the information systems. Furthermore, ongoing monitoring of data for quality conformance through a separate process is expensive and time consuming. Recognising this limitation and aiming to provide a practical-orient comprehensive approach, we propose a process centric quality focused system design incorporating data product quality, conformance monitoring and certification. In this paper we focus on the self certification of data quality based on our earlier work on the process centric framework for ongoing data quality monitoring.