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Data quality assessment in hydrological information systems

机译：水文信息系统中的数据质量评估

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摘要

The hydrological data fed to hydrological decision support systems might be untimely, incomplete, inconsistent or illogical due to network congestion, low performance of servers, instrument failures, human errors, etc. It is imperative to assess, monitor and even control the quality of hydrological data residing in or acquired from each link of a hydrological data supply chain. However, the traditional quality management of hydrological data has focused mainly on intrinsic quality problems, such as outlier detection, nullity interpolation, consistency, completeness, etc., and could not be used to assess the quality of application - that is, consumed data in the form of data supply chain and with a granularity of tasks. To achieve these objectives, we first present a methodology to derive quality dimensions from hydrological information system by questionnaire and show the cognitive differences in quality dimension importance, then analyze the correlations between the tasks, classify them into five categories and construct the quality assessment model with time limits in the data supply chain. Exploratory experiments suggest the assessment system can provide data quality (DQ) indicators to DQ assessors, and enable authorized consumers to monitor and even control the quality of data used in an application with a granularity of tasks.
机译：由于网络拥塞，服务器性能低下，仪器故障，人为错误等原因，馈入水文决策支持系统的水文数据可能不及时，不完整，不一致或不合逻辑。必须评估，监控甚至控制水文质量位于水文数据供应链各环节中或从中获取的数据。但是，传统的水文数据质量管理主要集中在固有的质量问题上，例如离群值检测，零值插值，一致性，完整性等，因此不能用于评估应用程序的质量-即，数据供应链的形式以及任务的细化程度。为了实现这些目标，我们首先提出一种方法，通过问卷从水文信息系统中得出质量维度，并显示出质量维度重要性方面的认知差异，然后分析任务之间的相关性，将其分为五类，并建立质量评估模型。数据供应链中的时间限制。探索性实验表明，评估系统可以为DQ评估人员提供数据质量（DQ）指标，并使授权用户能够监控甚至控制具有粒度任务的应用程序中使用的数据质量。

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