Multidimensional Contexts for Data Quality Assessment
The notion of data quality cannot be separated from the context in which the data is produced or used. Recently, a conceptual framework for capturing context-dependent data quality assessment has been proposed. According to it, a Database D is assessed w.r.t. a context which is modeled as an external system containing additional data, metadata and definitions of quality predicates. The instance D is "Put in context" via schema mappings; and after contextual processing of the data, a collection of alternative clean versions D of D is produced. The quality of D is measured in terms of its distance to this class.