Representing Software Engineering Models: The TAME Goal Oriented Approach
IEEE Transactions on Software Engineering
Anchoring data quality dimensions in ontological foundations
Communications of the ACM
Communications of the ACM
A product perspective on total data quality management
Communications of the ACM
Data quality and systems theory
Communications of the ACM
Microsoft repository version 2 and the open information model
Information Systems - Special issue on meta-modelling and methodology engineering
A Framework for Analysis of Data Quality Research
IEEE Transactions on Knowledge and Data Engineering
Data Quality Requirements Analysis and Modeling
Proceedings of the Ninth International Conference on Data Engineering
Architecture and Quality in Data Warehouses
CAiSE '98 Proceedings of the 10th International Conference on Advanced Information Systems Engineering
Design and Analysis of Quality Information for Data Warehouses
ER '98 Proceedings of the 17th International Conference on Conceptual Modeling
A Model for Data Warehouse Operational Processes
CAiSE '00 Proceedings of the 12th International Conference on Advanced Information Systems Engineering
Identifying Data Sources for Data Warehouses
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Data Quality in e-Business Applications
CAiSE '02/ WES '02 Revised Papers from the International Workshop on Web Services, E-Business, and the Semantic Web
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As a decision support information system, a data warehouse must provide high level quality of data and quality of service. In the DWQ project we have proposed an architectural framework and a repository of metadata which describes all the data warehouse components in a set of metamodels to which is added a quality metamodel, defining for each data warehouse metaobject the corresponding relevant quality dimensions and quality factors. Apart from this static definition of quality, we also provide an operational complement, that is a methodology on how to use quality factors and to achieve user quality goals. This methodology is an extension of the Goal-Question-Metric (GQM) approach, which allows to capture (a) the inter-relationships between different quality factors and (b) to organize them in order to fulfil specific quality goals. After summarizing the DWQ quality model, this paper describes the methodology we propose to use this quality model, as well as its impact on the data warehouse evolution.