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 observe that this definition is inherently and implicitly multidim...
Saved in:
| Main Author: | |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2008
|
| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/169/1/qdbmain.pdf http://eprints.utem.edu.my/id/eprint/169/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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]. |
|---|