{"accessLevel": "public", "bureauCode": ["010:12"], "contactPoint": {"@type": "vcard:Contact", "fn": "Farshid Rahmani", "hasEmail": "mailto:fzr5082@psu.edu"}, "description": "<p>This data release component contains model inputs including river basin attributes, weather forcing data, and simulated and observed river discharge.</p>", "distribution": [{"@type": "dcat:Distribution", "description": "The metadata original format", "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.5f9865abd34e198cb77ff086.xml", "format": "XML", "mediaType": "text/xml", "title": "Original Metadata"}, {"@type": "dcat:Distribution", "accessURL": "https://doi.org/10.5066/P97CGHZH", "description": "Landing page for access to the data", "format": "XML", "mediaType": "application/http", "title": "Digital Data"}], "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5f9865abd34e198cb77ff086", "keyword": ["inlandWaters", "Michigan", "United States", "NJ", "NM", "Utah", "USGS:5f9865abd34e198cb77ff086", "Texas", "NV", "VA", "AL", "Delaware", "Iowa", "North Carolina", "Nevada", "NC", "RI", "Rhode Island", "New Mexico", "GA", "OK", "environment", "WV", "Washington", "OR", "WY", "Oregon", "Maryland", "Virginia", "KS", "NY", "Kansas", "WA", "Wyoming", "New York", "SC", "modeling", "New Jersey", "WI", "OH", "TN", "South Carolina", "DE", "Mississippi", "Idaho", "Pennsylvania", "West Virginia", "TX", "deep learning", "Ohio", "Tennessee", "water temperature", "PA", "Wisconsin", "Massachusetts", "ID", "Maine", "MI", "UT", "US", "Oklahoma", "water resources", "MS", "machine learning", "streams", "Alabama", "MA", "MD", "Georgia", "IA", "ME"], "modified": "2020-12-09T00:00:00Z", "publisher": {"@type": "org:Organization", "name": "U.S. Geological Survey"}, "spatial": "-123.32988684, 30.1454932, -70.97964444, 48.90595739", "theme": ["geospatial"], "title": "Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 3 Model inputs"}