A Method for Measuring Data Quality in Data Integration

Mo Lin, Zheng Hua
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引用次数: 8

Abstract

This paper reports our method on measuring data quality in data integration. Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. Data quality is crucial for operational data integration. We posit that data-integration need to handle the measure of data quality. So, measuring data quality in data integration is one of worthy research topics. This paper focuses on believability, a major aspect of quality. At first, the author analyzes the background and content of this paper, then description of dimensions of believability is given, and we present our approach for computing believability based on metadata, finally the summary and prospect are listed. In this method, we make explicit use of lineage-based measurements and develop a precise approach to measuring data quality.
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数据集成中数据质量的度量方法
本文报道了一种测量数据集成中数据质量的方法。数据集成是将来自不同数据源的数据组合起来,并向用户提供这些数据的统一视图的问题。数据质量对于操作数据集成至关重要。我们假设数据集成需要处理数据质量的度量。因此,测量数据集成中的数据质量是值得研究的课题之一。本文的重点是可信度,这是质量的一个主要方面。首先对本文的研究背景和研究内容进行了分析,然后对可信度的维度进行了描述,提出了基于元数据的可信度计算方法,最后对本文的研究成果进行了总结和展望。在这种方法中,我们明确地使用了基于谱系的测量方法,并开发了一种精确的方法来测量数据质量。
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