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Open source software for visualization and quality control of continuous hydrologic and water quality sensor data

机译:开源软件,用于连续水文和水质传感器数据的可视化和质量控制

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It is common for in situ hydrologic and water quality data to be collected at high frequencies and for extended durations. These data streams, which may also be collected across many monitoring sites require infrastructure for data storage and management. The Observations Data Model (ODM), which is part of the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS), was developed as a standard data model in which to organize, store, and describe point observations data. In this paper we describe ODM Tools Python, an open source software application that allows users to query and export, visualize, and perform quality control post processing on time series of environmental observations data stored in an ODM database using automated Python scripting that records the corrections and adjustments made to data series in the quality control process and ensures data editing steps are traceable and reproducible. (C) 2015 The Authors. Published by Elsevier Ltd.
机译:通常要以较高的频率和较长的时间收集现场水文和水质数据。这些数据流(也可能跨许多监视站点收集)需要用于数据存储和管理的基础结构。观测数据模型(ODM)是标准数据模型,用于组织,存储和存储水文信息,该数据模型是大学水文科学公司联合会(CUAHSI)水文信息系统(HIS)的一部分。描述点观测数据。在本文中,我们将介绍ODM Tools Python,这是一个开放源代码软件应用程序,该应用程序允许用户使用自动Python脚本(记录更正)对存储在ODM数据库中的环境观测数据的时间序列进行查询和导出,可视化并执行质量控制后处理。在质量控制过程中对数据系列进行调整,并确保数据编辑步骤可追溯和可重复。 (C)2015作者。由Elsevier Ltd.发布

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