Joeseph SmithGeneral Programmer/Analyst
- University of Michigan 2009-2012: Informatics – Information Analysis/Data Mining Bachelor of Science
- Washtenaw Community College 2007-2009: Math and Computer Science Associates Degree
- Development of a Bayesian Network simulated via Markov Chain Monte Carlo sampling that effectively and efficiently closes the water balance of the Laurentian Great Lakes, utilizing multiple observation sources
- Development of a SQL (PostgreSQL) database for real-time remote sensing (buoy) data, making the data more accessible to scientists and stakeholders via a web interface.
- Processing of, collectively, multiple terabytes of data for web consumption (as above) and for scientific inquiries of multiple scientists and stakeholders.
- Refactored and redesigned software as necessary for increased efficiency and better documentation
- Aiding in and producing of publications and presentations to communicate scientific findings and software developments to the community and public
- Management of a website utilizing a Content Management System (CMS)
- Providing valuable input into the ongoing development of a sustainable and scalable Information Technology platform for scientific research and development
- Great Lakes Dashboard
- Lake Erie Harmful Algal Blooms (HABs) and Hypoxia data browsers covering routine manual sampling, automatic real-time, and model output data
- Map explorer for the Great Lakes Nonindigenous Species Information System (GLANSIS)
Smith, J.P., Miller, R.J., Muzzi, R.W., Constant, S.A., Beadle, K.S., Palladino, D.A., Johengen, T.H., Ruberg, S.A., An implementation of a database management system for real-time large-lake observations. Marine Technology Society Journal, 51(6).
Smith, J.P., and Gronewold, A.D., Development and analysis of a Bayesian water balance model for large lake systems. Submitted. E-print available on arXiv: https://arxiv.org/abs/1710.10161.
Gronewold, A.D., Bruxer, J., Durnford, D., Smith, J.P., Clites, A.H., Seglenieks, F., Qian, S.S., Hunter, T.S. and Fortin, V., 2016. Hydrological drivers of record‐setting water level rise on Earth’s largest lake system. Water Resources Research, 52(5), pp.4026-4042.
Smith, J.P., Hunter, T.S., Clites, A.H., Stow, C.A., Slawecki, T., Muhr, G.C. and Gronewold, A.D., 2016. An expandable web-based platform for visually analyzing basin-scale hydro-climate time series data. Environmental Modelling & Software, 78, pp.97-105. http://dx.doi.org/10.1016/j.envsoft.2015.12.005.
Ruberg, S.A., Constant, S.A., Muzzi, R.W., Miller, R.J., Smith, J.P., Utilization of PostgreSQL Database for Real-Time Western Lake Erie Data Storage and Dissemination. 60th Annual Conference of the International Association for Great Lakes Research, Detroit, Michigan, United States of America, May 15-19, 2017.
Smith, J.P., Hunter, T.S., and T.A. Slawecki. “MVC” environmental informatics software foundation for relationship-based collaborative science. 59th Annual Conference of the International Association for Great Lakes Research, University of Guelph, Ontario, Canada, June 6-10, 2016.
Smith, J.P., Hunter, T.S., and T.A. Slawecki. Tools of the Data Smithe’s Trade. 59th Annual Conference of the International Association for Great Lakes Research, University of Guelph, Ontario, Canada, June 6-10, 2016.