建立一个以结构化元数据为重点的原始和验证数据水质数据库

IF 2.4 4区 环境科学与生态学 Q2 WATER RESOURCES
Q. Plana, J. Alferes, Kevin Fuks, Tobias Kraft, T. Maruéjouls, E. Torfs, P. Vanrolleghem
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引用次数: 11

摘要

水体在线连续监测产生大量高频数据。这些数据的长期质量控制和适用性需要严格的存储和文档。为了成功地开展这些活动,必须建立一个数据库。这种数据库应易于储存和记录所有有关数据,并应易于用于进一步的数据评价和解释。本文提出了一种综合的水质数据数据库结构。它的目标是集中数据,标准化它们的格式,提供方便的访问,特别是以有效的方式记录与度量相关的所有相关信息(元数据)。对数据文件的强调不仅可以提供详细的测量历史信息(例如,在哪里,如何,何时,由谁测量的值),还可以提供设备历史信息(例如,传感器维护,校准/验证历史),人员(例如,经验),项目,采样地点等。因此,所建议的数据库结构为功能性数据存储和访问提供了一个健壮而有效的工具,允许将来使用花费很大的代价收集到的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a water quality database for raw and validated data with emphasis on structured metadata
On-line continuous monitoring of water bodies produces large quantities of high frequency data. Long-term quality control and applicability of these data require rigorous storage and documentation. To carry out these activities successfully, a database has to be built. Such a database should provide the simplicity to store and document all relevant data and should be easy to use for further data evaluation and interpretation. In this paper, a comprehensive database structure for water quality data is proposed. Its goal is to centralize the data, standardize their format, provide easy access, and, especially, document all relevant information (metadata) associated with the measurements in an efficient way. The emphasis on data documentation enables the provision of detailed information not only on the history of the measurements (e.g., where, how, when and by whom was the value measured) but also on the history of the equipment (e.g., sensor maintenance, calibration/validation history), personnel (e.g., experience), projects, sampling sites, etc. As such, the proposed database structure provides a robust and efficient tool for functional data storage and access, allowing future use of data collected at great expense.
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来源期刊
CiteScore
4.50
自引率
8.70%
发文量
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