{
  "accessLevel": "public",
  "bureauCode": [
    "010:12"
  ],
  "contactPoint": {
    "@type": "vcard:Contact",
    "fn": "Jordan S. Read",
    "hasEmail": "mailto:jread@usgs.gov"
  },
  "description": "This dataset includes \"test data\" compiled water temperature data from an instrumented buoy on Lake Mendota, WI and discrete (manually sampled) water temperature records from North Temperate Lakes Long-TERM Ecological Research Program (NTL-LTER; https://lter.limnology.wisc.edu/). The buoy is supported by both the Global Lake Ecological Observatory Network (gleon.org) and the NTL-LTER. The dataset also includes Lake Mendota model erformance as measured as root-mean squared errors relative to temperature observations during the test period. This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).",
  "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.5d925066e4b0c4f70d0d0599.xml",
      "format": "XML",
      "mediaType": "text/xml",
      "title": "Original Metadata"
    }
  ],
  "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5d925066e4b0c4f70d0d0599",
  "keyword": [
    "US",
    "USGS:5d925066e4b0c4f70d0d0599",
    "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": "-89.4836545048768, 43.0771195331357, -89.3674075050573, 43.1520341996861",
  "theme": [
    "geospatial"
  ],
  "title": "Process-guided deep learning water temperature predictions: 6a Lake Mendota detailed evaluation data"
}