Water Quality Data Collection through mWater Software
Advisor(s)
Dr. Melissa Lenczewski; Northern Illinois University
Discipline
Computer Science
Start Date
21-4-2021 9:10 AM
End Date
21-4-2021 9:25 AM
Abstract
Around the world, communities aim to make water quality data publicly accessible in order to help community members recognize how local water supplies may be impacting their health and environment. This project assists with this goal by taking on the critical tasks of collecting, storing, managing, analyzing, and publishing water quality data from the Kishwaukee River Water Quality Assessment Study in DeKalb, Illinois. The previous data management system for the study involved recording measurements on paper and then transferring data onto a digital spreadsheet. Due to the error-prone and inefficient nature of this process, this project instead utilizes mWater, a robust online platform for collecting and managing water quality data, to ensure data credibility. The new data management system includes transferring historical data records into the mWater database, creating data input surveys for future data collection, producing simple data visualizations that follow color visualization theory guidelines, and making improvements based on stakeholder feedback. As a result, reliable water quality data will be easily accessible and understandable to the public. This transparency is critical because the need for straightforward scientific communication is becoming increasingly apparent in today’s world with the COVID-19 pandemic and climate crisis.
Water Quality Data Collection through mWater Software
Around the world, communities aim to make water quality data publicly accessible in order to help community members recognize how local water supplies may be impacting their health and environment. This project assists with this goal by taking on the critical tasks of collecting, storing, managing, analyzing, and publishing water quality data from the Kishwaukee River Water Quality Assessment Study in DeKalb, Illinois. The previous data management system for the study involved recording measurements on paper and then transferring data onto a digital spreadsheet. Due to the error-prone and inefficient nature of this process, this project instead utilizes mWater, a robust online platform for collecting and managing water quality data, to ensure data credibility. The new data management system includes transferring historical data records into the mWater database, creating data input surveys for future data collection, producing simple data visualizations that follow color visualization theory guidelines, and making improvements based on stakeholder feedback. As a result, reliable water quality data will be easily accessible and understandable to the public. This transparency is critical because the need for straightforward scientific communication is becoming increasingly apparent in today’s world with the COVID-19 pandemic and climate crisis.