Model-Driven Component Generation for Families of Completeness Measures - Nurul A., Emran (2008)
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 observe that this definition is inherently and implicitly multidimensional: 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 life sciences. This leads to the idea of domain-specic families of completeness measures that users can choose from. Furthermore, individuals in the family can be specified as 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 measures can be supported in practice by extending the Quality View model [11].