ContDataQC: An R package and Shiny app for quality control of continuous water quality sensor data

IF 2.4 4区 计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Michael J. Pennino , Jen Stamp , Erik W. Leppo , David A. Gibbs , Britta G. Bierwagen
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Abstract

The ContDataQC R package is a free, open-source tool that was developed to help water quality monitoring programs perform quality control (QC) procedures on continuous sensor data. ContDataQC helps users speed up and standardize the QC process, minimize undetected data errors, and make full use of their sensor data. It has three main functions: generate QC reports to detect anomalies and erroneous data values, merge QC'd data files from different time periods, and generate time series plots and basic summary statistics. ContDataQC is currently configured to run on nine different parameters: air and water temperature, dissolved oxygen, conductivity, chlorophyll-a, air and water pressure, sensor depth, pH, turbidity, and salinity. Users can add new parameters and customize many of the requirements by editing a plain text configuration file. A web app version, through R Shiny, is available within the package or via a weblink. If accessed via the URL, it will not require the installation of R software. In this paper, we describe the main functions of ContDataQC and discuss how it is being applied in long-term regional monitoring networks for streams and lakes. Both the R Shiny web app and the R package are for users who have no existing workflow for sensor data and wish to adopt the approach of ContDataQC (which has a particular organizational scheme and sequential workflow). People without R coding experience can use the Shiny app, which has a more user-friendly interface, while users who are proficient in R may choose to use the code package.

Abstract Image

ContDataQC:一个R包和闪亮的应用程序,用于连续水质传感器数据的质量控制
ContDataQC R包是一个免费的开源工具,旨在帮助水质监测程序对连续传感器数据执行质量控制(QC)程序。ContDataQC帮助用户加快和规范QC过程,最大限度地减少未检测到的数据错误,并充分利用他们的传感器数据。它有三个主要功能:生成QC报告以检测异常和错误数据值,合并不同时间段的QC数据文件,生成时间序列图和基本汇总统计。ContDataQC目前配置为9个不同的参数:空气和水温,溶解氧,电导率,叶绿素-a,空气和水压,传感器深度,pH值,浊度和盐度。用户可以通过编辑纯文本配置文件来添加新参数和自定义许多需求。通过R Shiny的web应用程序版本可以在包中或通过webblink获得。如果通过URL访问,则不需要安装R软件。本文介绍了ContDataQC的主要功能,并讨论了它在河流和湖泊长期区域监测网络中的应用。R Shiny web应用程序和R包都是为那些没有现有传感器数据工作流并希望采用ContDataQC方法(具有特定的组织方案和顺序工作流)的用户提供的。没有R编程经验的人可以使用Shiny的app,它的界面更加人性化,而精通R的用户可能会选择使用代码包。
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来源期刊
SoftwareX
SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
5.50
自引率
2.90%
发文量
184
审稿时长
9 weeks
期刊介绍: SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.
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