{"accessLevel": "public", "bureauCode": ["010:12"], "contactPoint": {"@type": "vcard:Contact", "fn": "Jordan S. Read", "hasEmail": "mailto:jread@usgs.gov"}, "description": "This dataset provides model specifications used to estimate water temperature from a process-based model (Hipsey et al. 2019). The format is a single JSON file indexed for each lake based on the \"site_id\". 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.5d8a2257e4b0c4f70d0ae513.xml", "format": "XML", "mediaType": "text/xml", "title": "Original Metadata"}], "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5d8a2257e4b0c4f70d0ae513", "keyword": ["biota", "inlandWaters", "United States", "environment", "US", "MN", "reservoirs", "deep learning", "Minnesota", "machine learning", "temperature", "modeling", "climate change", "Wisconsin", "WI", "hybrid modeling", "thermal profiles", "water", "USGS:5d8a2257e4b0c4f70d0ae513", "temperate lakes"], "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: 2 Model configurations (lake metadata and parameter values)"}