1 Detection and Resolution of Data Inconsistencies, and Data Integration using Data Quality Criteria

Abstract — In the processes and optimization of information integration, such as query processing, query planning and hierarchical structuring of results to the user, we argue that user quality priorities, data inconsistencies and data quality differences among the participating sources have not been fully addressed. We propose the development of a Data Quality Manager (DQM) to establish communication between the process of integration of information, the user and the application, to deal with semantic heterogeneity and data quality. DQM will contain a Reference Model, a Measurement Model, and an Assessment Model to define the quality criteria, the metrics and the assessment methods. DQM will also help in query planning by considering data quality estimations to find the best combination for the execution plan. After query execution, and detection of inconsistent data, data quality might also be used to perform data inconsistency resolution. Integration and ranking of query results using quality criteria defined by the user will be an outcome of this process