Recent Projects
EnviroTox Database & ecoTTC
The Data Science Institute is part of an international collaboration that developed the EnviroTox Database, (a collection of approximately 91,000 unique ecotoxicological records, 4,000 chemicals and 1,500 species) and an on-line analytical tool that aides in the assessment risk to aquatic organisms. This collaboration includes scientists from multiple governments, industries and academic institutions and has been endorsed by the Joint Research Centre (JRC), a unit of the European Commission. The EnviroTox Database is hosted at Middle Tennessee State University. The EnviroTox Database and the analytical tool are publicly available at envirotoxdatabase.org MTSU Involvement: Ryan Otter, Josh Phillips
Publications:
- Connors K., Beasley A., Baron M., Belanger S., Bonnell M., Brill J., de Zwart D., Kienzler A., Krailler J., Otter R.R., Phillips J., Embry M. 2019. Creation of a curated aquatic toxicology database: EnviroTox. Environmental Toxicology and Chemistry. 38(5):1062-1073. pdf
- Barron M.G., Otter R.R., Connors K.A., Kienzler A., Embry M.R. 2021. Ecological Thresholds of Toxicological Concern: History Development, and Application. Frontiers in Toxicology. 3:640183. DOI: 10.3389/ftox.2021.640193. pdf
- Belanger S.E., Beasley A., Brill J.L., Krailler J., Connors K.A., Carr G.J., Embry M., Barron M.G., Otter R.R., Kienzler A. 2021. Comparison of PNEC derivation logic flows under example regulatory schemes and implications for ecoTTC. Regulatory Toxicology and Pharmacology. 123:104933.
Criteria for Reporting and Evaluating Exposure Datasets (CREED)
The Data Science Institute is part of an internal collaboration tasked with developing the first ever framework to standardize how environmental scientists evaluate data when calculating the risk to the environmental from pollution sources. This collaboration includes scientists from multiple governments, industries and academic institutions. The first publications of this work are expected earlier in 2023. MTSU Involvement: Ryan Otter
An Advanced Water Quality Monitoring Program to Assess Farming Practices
The Data Science Institute, in collaboration with the Department of Biology, aim to improve water quality caused by impairments, including sediment, nutrients, and bacteria. Funded by the US Department of Agriculture, this project is focused on the implementation of advanced monitoring sondes to advance our understanding of the impact of specific farming techniques on water quality, in near real-time. MTSU Involvement: Frank Bailey, Ryan Otter
Tennessee’s Ecologically At-Risk Streams (TEARS)
The susceptibility of Tennessee’s Appalachian Mountains to anthropogenic stressors has remained largely uninvestigated likely due to a lack of known point source contamination. However, a growing body of scientific evidence suggests that inputs from the atmosphere can lead to concerning levels of contamination. MTSU was the lead on this collaborative project (State of Tennessee, National Parks Service, and multiple Universities) where we investigated the risk of multiple contaminants in water, fish, and other critters (like spiders). This work was the first to establish baseline concentrations of PCBs, pesticides, dioxins, furans, and phthalates in Tennessee’s Appalachian Mountains and showed that even remote locations can be susceptible to pollution. MTSU Involvement: Ryan Otter
Publications:
- **Olson C.I., **Beaubien G.B., McKinney A.D., Otter R.R. 2019. Identifying contaminants of potential concern in remote headwater streams of Tennessee’s Appalachian Mountains. Environmental Monitoring and Assessment. 191:176. DOI: 10.1007/s10661-019-7305-7. pdf
- **Beaubien G.B., **Olson C.I., *Todd A. Otter R.R. 2020. The spider exposure pathway and the potential risk to arachnivorous birds. Environmental Toxicology and Chemistry. 39(11):2314-2324. pdf
Multi-Senor Data System
The Data Science Institute developed a Multi-Sensor Data System (MSDS) for the integration of multiple water quality datasets. This system was designed to automate the ingestion of varying files into a data lake, process into a data warehouse and marts, and serve up the results via a dashboard, in minutes. This system was built using AWS serverless technologies with a focus on low cost and maintenance, with high performance and reliability. It is currently deployed and being used by partners in the US Environmental Protection Agency and the US Geological Survey. MTSU Involvement: Ryan Otter, Alex Antonison
Remedy Effectiveness Assessments in the Great Lakes
Great Lakes Areas of Concern (AOC) are contaminated by decades of industrial and municipal discharges, combined with sewer overflows, and urban and agricultural non-point source runoff. Contaminants of concern in Great Lakes AOCs include mercury, polychlorinated biphenyls, polycyclic aromatic hydrocarbons, metals, industrial organics, oils, and greases. The Data Science Institute is involved with multiple Federal Agencies to help in the design, analysis, and interpretation of the data needed to determine the proper remedies to use to help clean up these sites and the effectiveness of those remedies. MTSU Involvement: Ryan Otter, Alex Antonison
Publications:
Opioid Response
In collaboration with the Center for Health and Human Services at MTSU, the Data Science Institute is providing an array of data services to prevent and reduce drug misuse and addiction among youth and adults; and to provide education, communication, and awareness of resources in Wilson County Tennessee. MTSU Involvement: Cindy Chaffin, Kahler Stone, Jeff Stark, Sara Shirley, Ryan Otter
DataScience4
An in-house build, DataScience4 is a platform high quality expert-curated data in the hands of teachers and students so they can learn by doing not watching. Check it out: www.datascience4.org MTSU Involvement: Ryan Otter, Alex Murphy, Cheri Burt
