数据质量指标要求

Bernd Heinrich, Diana Hristova, Mathias Klier, Alexander Schiller, Michael Szubartowicz
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引用次数: 76

摘要

数据质量,特别是数据质量的评估在研究和实践中都得到了广泛的讨论。为了在不确定的情况下支持以经济为导向的数据质量管理和决策制定,有必要通过有充分依据的指标来评估数据质量水平。然而,如果没有充分定义,这些指标可能会导致错误的决策和经济损失。因此,基于面向决策的框架,我们提出了一组数据质量度量的五个要求。这些要求与旨在支持面向经济的数据质量管理和不确定情况下的决策制定的度量相关。通过评估不同数据质量维度的五个数据质量指标,我们进一步证明了这些需求的适用性和有效性。此外,我们还讨论了应用所提出的需求时的实际含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Requirements for Data Quality Metrics
Data quality and especially the assessment of data quality have been intensively discussed in research and practice alike. To support an economically oriented management of data quality and decision making under uncertainty, it is essential to assess the data quality level by means of well-founded metrics. However, if not adequately defined, these metrics can lead to wrong decisions and economic losses. Therefore, based on a decision-oriented framework, we present a set of five requirements for data quality metrics. These requirements are relevant for a metric that aims to support an economically oriented management of data quality and decision making under uncertainty. We further demonstrate the applicability and efficacy of these requirements by evaluating five data quality metrics for different data quality dimensions. Moreover, we discuss practical implications when applying the presented requirements.
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