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High-Resolution, Interagency Biosurveillance of Threatened Surface Waters in the United States

Summary

Advances in information technology now provide large volume, high-frequency data collection which may improve real-time biosurveillance and forecasting. But, big data streams present challenges for data management and timely analysis. As a first step in creating a data science pipeline for translating large datasets into meaningful interpretations, we created a cloud-hosted PostgreSQL database that collates climate data served from PRISM (https://climatedataguide.ucar.edu/climate-data) and water-quality data from the National Water Quality Portal (https://www.waterqualitydata.us/) and NWIS (https://waterdata.usgs.gov/nwis; fig 1). Using Python-based code, these data streams are queried and updated every 24 hours, and the spatial and [...]

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“Processing steps to create a Digital Ocean PostgreSQL database ”
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Processing steps to create a Digital Ocean PostgreSQL database
Processing steps to create a Digital Ocean PostgreSQL database

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  • Community for Data Integration (CDI)

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