{
  "accessLevel": "public",
  "bureauCode": [
    "010:12"
  ],
  "contactPoint": {
    "@type": "vcard:Contact",
    "fn": "Jordan S. Read",
    "hasEmail": "mailto:jread@usgs.gov"
  },
  "description": "Observed water temperatures from 1980-2018 were compiled for 68 lakes in Minnesota and Wisconsin (USA). These data were used as training data for process-guided deep learning models and deep learning models, and calibration data for process-based models. The data are formatted as a single csv (comma separated values) file with attributes corresponding to the unique combination of lake identifier, time, and depth. Data came from a variety of sources, including the Water Quality Portal, the North Temperate Lakes Long-Term Ecological Research Project, and digitized temperature records from the MN Department of Natural Resources.",
  "distribution": [
    {
      "@type": "dcat:Distribution",
      "accessURL": "http://dx.doi.org/10.5066/P9AQPIVD",
      "description": "Landing page for access to the data",
      "format": "XML",
      "mediaType": "application/http",
      "title": "Digital Data"
    },
    {
      "@type": "dcat:Distribution",
      "description": "The metadata original format",
      "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.5d8a47bce4b0c4f70d0ae61f.xml",
      "format": "XML",
      "mediaType": "text/xml",
      "title": "Original Metadata"
    }
  ],
  "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5d8a47bce4b0c4f70d0ae61f",
  "keyword": [
    "MN",
    "Minnesota",
    "US",
    "USGS:5d8a47bce4b0c4f70d0ae61f",
    "United States",
    "WI",
    "Wisconsin",
    "biota",
    "climate change",
    "deep learning",
    "environment",
    "hybrid modeling",
    "inlandWaters",
    "machine learning",
    "modeling",
    "reservoirs",
    "temperate lakes",
    "temperature",
    "thermal profiles",
    "water"
  ],
  "modified": "2020-08-20T00:00:00Z",
  "publisher": {
    "@type": "org:Organization",
    "name": "U.S. Geological Survey"
  },
  "spatial": "-94.2609062307949, 42.5692312672573, -87.9475441739278, 48.6427837911633",
  "theme": [
    "geospatial"
  ],
  "title": "Process-guided deep learning water temperature predictions: 4c All lakes historical training data"
}