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.

Impact/Purpose

Continuous sensors that measure a variety of water quality parameters, such as temperature, water level, and dissolved oxygen (DO), at high frequencies (such as every 30-minutes) continue to become more affordable and accessible. The sensors capture temporal patterns and episodic events that may otherwise be missed if measurements can only be taken during a limited numbers of site visits. Managing the data and performing quality control (QC) checks to detect anomalies and erroneous data values can be daunting, especially for users that lack prior experience working with sensors. Moreover, the iterative process of QC editing can be tedious and challenging, and levels of rigor vary. This tools helps to standardize and speed up QC of continuous sensor data; improve documentation of the QC process; reduce missed errors; and provide outputs that are in a standardized format to facilitate further analysis and sharing. 

Citation

Pennino, Michael J., J. Stamp, E. Leppo, D. Gibbs, AND Britta G. Bierwagen. ContDataQC: An R package and Shiny app for quality control of continuous water quality sensor data. Elsevier B.V., Amsterdam, NETHERLANDS, 30:102124, (2025). [DOI: 10.1016/j.softx.2025.102124]

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