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- W2770673165 abstract "When hydrologic scientists are looking for data to use in their data models relevant to their research area, they encounter a bottleneck when trying to collect relevant information, sometimes they might not know of all the available sources. Great Lakes Monitoring (GLM) collects data from 5 different state and federal agencies that take measurements on nutrients, geochemicals, contaminants, among other water quality data that directly affect the water health in the Great Lakes. In this paper, we describe the cyberinfrastructure that has been implemented in order to address this issue. To accomplish this, it cleans and organizes the data into a semi-standardized schema, ingests the data to a database, and takes advantage of a user interface for data visualizations. On top of this, trends for selected parameters can be observed within a map, data can be searched, downloaded in various formats and compared across different locations within the Great Lakes." @default.
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- W2770673165 date "2017-10-01" @default.
- W2770673165 modified "2023-09-24" @default.
- W2770673165 title "Monitoring Water Quality in the Great Lakes Leveraging Geo-Temporal Cyberinfrastructure" @default.
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- W2770673165 doi "https://doi.org/10.1109/escience.2017.50" @default.
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