dansullivanblk's data-quality [3 articles]

Abstract

Data consumers assess quality within specific business contexts or decision tasks. The same data resource may have an acceptable level of quality for some contexts but this quality may be unacceptable for other contexts. However, existing data quality metrics are mostly derived impartially, disconnected from the specific contextual characteristics. This study argues for the need to revise data quality metrics and measurement techniques to incorporate and better reflect contextual assessment. It contributes to that end by developing new metrics for assessing ...

Abstract

Information quality (IQ) is critical in organizations. Yet, despite a decade of active research and practice, the field lacks comprehensive methodologies for its assessment and improvement. Here, we develop such a methodology, which we call AIM quality (AIMQ) to form a basis for IQ assessment and benchmarking. The methodology is illustrated through its application to five major organizations. The methodology encompasses a model of IQ, a questionnaire to measure IQ, and analysis techniques for interpreting the IQ measures. We develop and ...

Abstract

Today many organizations are facing the need to integrate multiple, previously independent but semantically related information sources. Although often the quality and integrity of the data at a single information source itself is a problem, issues and problems regarding the quality and integrity of integrated data have been mainly neglected by approaches to data integration. As recent studies show, this raises severe problems for global applications that depend on the reliability of the integrated data. In this paper we focus on ...