Event Title

Water Quality Data Collection through mWater Software

Session Number

Project ID: CMPS 03

Advisor(s)

Dr. Melissa Lenczewski, Northern Illinois University

Discipline

Computer Science

Start Date

20-4-2022 11:25 AM

End Date

20-4-2022 11:50 AM

Abstract

Easily accessible water quality data is crucial in showing how local water supplies may be impacting public health and the environment for communities around the world. This project takes 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 using mWater, a robust online platform for collecting and managing water quality data. The data management system includes transferring historical data records into the mWater database, creating data collection surveys, and producing data visualizations that are available to the public. The mWater data management and publication system have also been adapted to cenote water quality studies conducted in Mexico through the NIU REU summer research program. Data 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. Further, the project involved collecting and running Kishwaukee River water samples through Exact Micro 20 water quality tests. This field and lab work provided valuable insight into how the mWater data management system could be improved, demonstrating the importance of interdisciplinary collaboration between computer science and biology.

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Apr 20th, 11:25 AM Apr 20th, 11:50 AM

Water Quality Data Collection through mWater Software

Easily accessible water quality data is crucial in showing how local water supplies may be impacting public health and the environment for communities around the world. This project takes 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 using mWater, a robust online platform for collecting and managing water quality data. The data management system includes transferring historical data records into the mWater database, creating data collection surveys, and producing data visualizations that are available to the public. The mWater data management and publication system have also been adapted to cenote water quality studies conducted in Mexico through the NIU REU summer research program. Data 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. Further, the project involved collecting and running Kishwaukee River water samples through Exact Micro 20 water quality tests. This field and lab work provided valuable insight into how the mWater data management system could be improved, demonstrating the importance of interdisciplinary collaboration between computer science and biology.