数据质量:经验主义的作用

S. Sadiq, T. Dasu, X. Dong, J. Freire, I. Ilyas, S. Link, Renée J. Miller, Felix Naumann, Xiaofang Zhou, D. Srivastava
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引用次数: 37

摘要

我们概述了在数据质量研究中促进经验主义的行动呼吁。这些行动要点源于对数据质量研究现状的分析。景观展示了数据质量研究中与度量类型和方法范围相关的经验主义的两个维度。我们的研究表明,存在从真实数据到合成数据的数据连续体,这对如何评估数据质量方法具有影响。经验主义的维度及其相互关系提供了一种定位数据质量研究的方法,并有助于揭示局限性、差距和机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Quality: The Role of Empiricism
We outline a call to action for promoting empiricism in data quality research. The action points result from an analysis of the landscape of data quality research. The landscape exhibits two dimensions of empiricism in data quality research relating to type of metrics and scope of method. Our study indicates the presence of a data continuum ranging from real to synthetic data, which has implications for how data quality methods are evaluated. The dimensions of empiricism and their inter-relationships provide a means of positioning data quality research, and help expose limitations, gaps and opportunities.
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