Toward quality data: An attribute-based approach

A quality perspective in data resource management is critical. Because users have different criteria for determining the quality of data, we propose tagging data at the cell level with quality indicators, which are objective characteristics of the data and its manufacturing process. Based on these i...

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Bibliographic Details
Published in:Decision Support Systems 1995-03, Vol.13 (3), p.349-372
Main Authors: Wang, Richard Y., Reddy, M.P., Kon, Henry B.
Format: Article
Language:English
Subjects:
Data analysis
Data base management systems
Data management
Data quality
Database design
Decision support systems
Information systems
Information technology
Management
Metadata
Requirements analysis
Software quality
Studies
Systems design
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Summary:A quality perspective in data resource management is critical. Because users have different criteria for determining the quality of data, we propose tagging data at the cell level with quality indicators, which are objective characteristics of the data and its manufacturing process. Based on these indicators, the user may assess the data's quality for the intended application. This paper investigates how such quality indicators may be specified, stored, retrieved, and processed. We propose an attribute-based data model, query algebra, and integrity rules that facilitate cell-level tagging as well as the processing of application data that is augmented with quality indicators. An ER-based data quality requirements analysis methodology is proposed for specification of the kinds of quality indicator to be modeled.
ISSN:0167-9236
1873-5797
DOI:10.1016/0167-9236(93)E0050-N