Research On The Consistency Of Data Warehouse System Metadata Based On Description Logics

The effective management of metadata is indispensable to successfully operate and use the data warehouse system. The quality management of metadata is an important part of metadata management. Only in the description of high quality metadata can high quality data work sufficiently. The consistency management of metadata is an important part of the quality management of metadata. The inconsistencies of metadata content can greatly influence the validity and accuracy of the data warehouse system processing data, thus greatly influence the stability and reliability of the data warehouse system. The research related to metadata consistency is still in its infancy, there is no systematic research about metadata consistency taking into account common metadata management specifications. This dissertation researches systematically the problems of metadata consistency in the data warehouse system based on common metadata exchange standard-Common Warehouse Metamodel(CWM). Our research can be favorably exploited for developing intelligent system that enforces metadata consistency in the data warehouse system. This system supports the automatic detection and semi-automatic resolution of metadata inconsistencies, so as to provide support for the development and integration of the components of data warehouse systems, thus improve the stability and reliability of data warehouse system.Inconsistency management is a complex process consisting of different activities. It is a well-studied process within software engineering. Inconsistency management in the CWM metadata context is quite complicated due to several reasons. The most obvious reason is the missing formal semantics for the CWM metadata and metamodel. In our opinion, the inconsistency management of the CWM metadata must rely on a powerful formalism enabling the precise definition, detection and resolution of inconsistencies. We distil a set of key criteria. The requirements for each of these criteria can be used to evaluate a formalism supporting the detection and resolution of CWM metadata inconsistencies.Description Logic(DL) is a two-variable fragment of first-order predicate logic, defining a family of logic languages, offering a classification task based on the subconcept-superconcept relationship. DLs are very suited for reasoning about hierarchies and about the satisfiability of knowledge bases. Different DL systems are developed. We discover that DLs and DL systems are suited for the detection and resolution of CWM metadata inconsistencies. DLs are validated against our key criteria in three successive steps. First, we investigate if it is possible to describe the abstract syntax and semantic of the CWM metadata. Second, we show how inconsistencies can be detected using this formalism. Finally, we investigate if it is possible to resolve inconsistencies using DLs and DL systems.The contributions of this dissertation are: (1) distilling a set of criteria used to evaluate a static inconsistency detection and resolution formalism that serves as the basis for inconsistency management tool for the CWM metadata, and validating our formalism against these key criteria. (2) choosing DLs as the formalism for data warehouse system metadata based on CWM metadata exchange standard, and presenting a DL for the description of the CWM metadata and metamodel. (3) distinguishing metadata consistency into horizontal consistency and evolution consistency, and presenting the approach for formalizing the CWM metadata and metamodel in these two consistency context. (4) presenting the approach for detecting metadata inconsistencies using the query and reasoning ability provided by DLs. (5) presenting the approach for resolving metadata inconsistencies using inconsistency resolution rules in DLs.