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

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.

Authors

Institutions

Publication Details

Journal
SoftwareX
Published
2025-03-22
DOI
https://doi.org/10.1016/j.softx.2025.102124
Citations
2
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
1.63

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Jen Stamp, Michael J. Pennino, Britta Bierwagen, Erik W. Leppo et al.
2 citations
SoftwareX
Water Quality Monitoring Technologies
1.63
article

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

Jen Stamp, Michael J. Pennino, Britta Bierwagen, Erik W. Leppo, David A. Gibbs
article en
2 citations

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.

SoftwareXVol. 30
Environmental Protection Agency (US), World Resources Institute (US), Tetra Tech (United States) (US)
U.S. Environmental Protection Agency, Office of Research and Development
Clean water and sanitation
Openalex Percentile: Top 18%
Water Quality Monitoring Technologies
1.63
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.