Model-driven component generation for families of completeness measures

Completeness is a well-understood dimension of data quality. In particular, measures of coverage can be used to assess the completeness of a data source, relative to some universe, for instance a collection of reference databases. We dimensional: in principle, one can compute measures of coverage that are expressed as a combination of subset of the attributes in the data source schema. This generalization can be useful in several application domains, notably in the ilies of completeness measures that users can choose from. OLAP-type queries on a dimensional schema. In this paper we describe an initial data architecture to support and validate the idea, and show how dimensional completeness measure's can be supported in practice by extending the Quality View model [11].