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Utilizing Qlik to visualize the multiagency spatiotemporal data driving effects-based monitoring
Citation:
Launspach, J., H. Buffum, J. Frisch, H. Helgen, W. Melendez, AND B. Blackwell. Utilizing Qlik to visualize the multiagency spatiotemporal data driving effects-based monitoring. International Association of Great Lakes Research (IAGLR) Virtual Conference, Duluth, MN, May 17 - 21, 2021. https://doi.org/10.23645/epacomptox.14755467
Impact/Purpose:
Chemical and biological data were collected by multiple agencies including USEPA, USGS, USFWS, USACOE, and NOAA focused on the potential effects of emerging contaminants in the Great Lakes as part of the Great Lakes Restoration Initiative (GLRI). To integrate this data across agencies, datasets from each agency are being entered into a MYSQL database. Once in the database, Qlik software is used to visualize and help interpret the data. This provides a way to browse data and provides a format for future public release of this multiagency database.
Description:
The Great Lakes Restoration Initiative (GLRI) began in 2010 aimed at protecting and restoring the country’s largest freshwater resource. One component of the GLRI involves consideration of the adverse impacts of complex mixtures of legacy chemicals and contaminants of emerging concern (CECs) on Great Lakes fish and wildlife. To address this issue, a multi-agency research consortium with technical expertise in the monitoring/surveillance of environmental contaminants and biological effects in ecologically-relevant species was assembled. The partners include U.S. Environmental Protection Agency, U.S. Geological Survey, National Ocean and Atmospheric Administration, U.S. Fish and Wildlife Service, U.S. Army Corps of Engineers, Clarkson University and St. Cloud State University. The approach chosen by the team to address the multifaceted challenge of complex mixture assessment involves linking extensive analytical chemistry measurements to effects-based monitoring (EBM) data collected using different types of biological systems. Through these studies, the consortium has and continues to generate a large amount of diverse chemical and biological data. This data is consolidated and formatted using an extensive quality assurance and quality-controlled process. Qlik was originally used as a Business Intelligence tool and has been repurposed throughout the QA/QC process to identify outliers. Once the data has been vetted and placed in the project’s MySQL database, it is exported to create Qlik front-end applications. The Qlik software allows for visualizing large datasets at one time in a variety of different formats. These formats can be custom built to meet the clients’ needs and allow for filtering and exporting to an image or table for further analysis. The goal, once approved, will be to make this and other Qlik applications available publicly for other researchers to use in the Great Lakes region. The contents of this abstract neither constitute nor necessarily reflect US EPA policy.
URLs/Downloads:
DOI: Utilizing Qlik to visualize the multiagency spatiotemporal data driving effects-based monitoring