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From Data Quality to Big Data Quality

机译:从数据质量到大数据质量

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This article investigates the evolution of data quality issues from traditional structured data managed in relational databases to Big Data. In particular, the paper examines the nature of the relationship between Data Quality and several research coordinates that are relevant in Big Data, such as the variety of data types, data sources and application domains, focusing on maps, semi-structured texts, linked open data, sensor & sensor networks and official statistics. Consequently a set of structural characteristics is identified and a systematization of the a posteriori correlation between them and quality dimensions is provided. Finally, Big Data quality issues are considered in a conceptual framework suitable to map the evolution of the quality paradigm according to three core coordinates that are significant in the context of the Big Data phenomenon: the data type considered, the source of data, and the application domain. Thus, the framework allows ascertaining the relevant changes in data quality emerging with the Big Data phenomenon, through an integrative and theoretical literature review.
机译:本文研究了数据质量问题从关系数据库中管理的传统结构化数据到大数据的演变。特别是,本文研究了数据质量与大数据中若干相关研究坐标之间关系的性质,例如各种数据类型,数据源和应用领域,重点是地图,半结构化文本,链接开放数据,传感器和传感器网络以及官方统计数据。因此,识别出一组结构特征,并提供了它们与质量尺寸之间的后验相关性的系统化。最后,在一个概念框架中考虑了大数据质量问题,该概念框架适合根据在大数据现象的背景下很重要的三个核心坐标来映射质量范式的演变:所考虑的数据类型,数据源和应用程序域。因此,该框架可以通过综合和理论文献综述来确定随着大数据现象而出现的数据质量的相关变化。

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