Information Content of DQAF Indicators - Empirical Entropy Analysis

Mićo Mrkaić
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引用次数: 3

Abstract

The study presents an analysis of the information content of IMF’s Data Quality Assessment Framework (DQAF) indicators. There are significant differences in the quantity of information between DQAF dimensions and sub-dimensions. The most informative DQAF dimension is accessibility, followed by the prerequisites of quality and accuracy and reliability. The least informative DQAF dimensions are serviceability and assurances of integrity. The implication of these findings is that the current DQAF indicators do not maximize the amount of information that could be obtained during data ROSC missions. An additional set of assessments that would refine the existing DQAF indicators would be beneficial in maximizing the information gathered during data ROSC mission. The entropy of DQAF indicators could also be used in the construction of a cardinal index of data quality.
DQAF指标的信息含量——经验熵分析
本研究对IMF数据质量评估框架(DQAF)指标的信息内容进行了分析。DQAF维度与子维度之间的信息量存在显著差异。信息量最大的DQAF维度是可访问性,其次是质量、准确性和可靠性的先决条件。信息量最少的DQAF维度是可服务性和完整性保证。这些调查结果的含义是,目前的DQAF指标并没有最大限度地提高在数据ROSC任务期间可以获得的信息量。一套额外的评估将改进现有的质量保证框架指标,这将有助于最大限度地利用在数据ROSC任务期间收集的信息。DQAF指标的熵也可用于构建数据质量的基本指标。
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