Modeling Context for Data Quality Management

The importance of context for data quality (DQ) has been shown decades ago and is widely accepted. Early approaches and surveys defined DQ as fitness for use and showed the influence of context on DQ. However, very few proposals for context modeling can be found in DQ literature. This paper reviews many context components suggested in the literature and proposes a context model tailored for DQ management. Through a running example, and relying on the literature reviewed, we illustrate the applicability of the model.

Automated summary

This paper highlights the importance of context for data quality and proposes a context model specifically designed for data quality management.