@prefix dcat: <http://www.w3.org/ns/dcat#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix gsp: <http://www.opengis.net/ont/geosparql#> .
@prefix locn: <http://www.w3.org/ns/locn#> .
@prefix vcard: <http://www.w3.org/2006/vcard/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da> a dcat:Dataset ;
    dct:description "This dataset includes model inputs that describe local weather conditions for Lake Mendota, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded estimates (all other time periods). There are two comma-delimited files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see \"Predictions\" and \"pb0\" model type for the source of this prediction). 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)." ;
    dct:identifier "53d78393-de81-4231-b437-548df5044dbc" ;
    dct:issued "2025-11-21T18:18:13.211311"^^xsd:dateTime ;
    dct:modified "2020-08-20"^^xsd:date ;
    dct:publisher <https://data.amerigeoss.org/organization/727dbdd5-3f98-4ac0-9d28-5e344558139b> ;
    dct:spatial [ a dct:Location ;
            locn:geometry "POLYGON ((-89.4837 43.0771, -89.3674 43.0771, -89.3674 43.1520, -89.4837 43.1520, -89.4837 43.0771))"^^gsp:wktLiteral ] ;
    dct:title "Process-guided deep learning water temperature predictions: 3a Lake Mendota inputs" ;
    dcat:contactPoint [ a vcard:Organization ;
            vcard:fn "U.S. Geological Survey (Point of Contact)" ;
            vcard:hasEmail <mailto:jread@usgs.gov> ] ;
    dcat:distribution <https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/477979d8-49a6-4825-8847-de8ea25b8059>,
        <https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/9adffcc5-c8ee-4e3a-9213-e6269c383ab2>,
        <https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/9ba555d0-7dd0-43be-8a03-37679382914a>,
        <https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/9ca6a8e1-05d7-48cd-813d-9a5762912b9f>,
        <https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/e3024286-9836-45f0-b18d-b5f99d6f756f>,
        <https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/e4defd86-2a38-41eb-9296-add4f11111c8> ;
    dcat:keyword "amerigeo",
        "amerigeoss",
        "ckan",
        "climate-change",
        "deep-learning",
        "geo",
        "geoss",
        "hybrid-modeling",
        "machine-learning",
        "modeling",
        "national",
        "north-america",
        "reservoirs",
        "temperate-lakes",
        "temperature",
        "thermal-profiles",
        "united-states",
        "us",
        "usgs-5d98e0c4e4b0c4f70d1186f1",
        "water" ;
    dcat:theme <%7Bgeospatial%7D> .

<https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/477979d8-49a6-4825-8847-de8ea25b8059> a dcat:Distribution ;
    dct:description "CSDGM IMPORT ERROR: No digtinfo/formcont" ;
    dct:issued "2022-01-25T19:25:53.776337"^^xsd:dateTime ;
    dct:modified "2025-11-21T18:18:13.198761"^^xsd:dateTime ;
    dct:title "two comma separated text files" ;
    dcat:accessURL <http://dx.doi.org/10.5066/P9AQPIVD> .

<https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/9adffcc5-c8ee-4e3a-9213-e6269c383ab2> a dcat:Distribution ;
    dct:issued "2022-01-25T19:25:53.776350"^^xsd:dateTime ;
    dct:modified "2025-11-21T18:18:13.199960"^^xsd:dateTime ;
    dct:title "Web Resource" ;
    dcat:accessURL <http://dx.doi.org/10.1029/2003JD003823> .

<https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/9ba555d0-7dd0-43be-8a03-37679382914a> a dcat:Distribution ;
    dct:issued "2022-01-25T19:25:53.776344"^^xsd:dateTime ;
    dct:modified "2025-11-21T18:18:13.199185"^^xsd:dateTime ;
    dct:title "Web Resource" ;
    dcat:accessURL <http://dx.doi.org/10.5066/P9AQPIVD> .

<https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/9ca6a8e1-05d7-48cd-813d-9a5762912b9f> a dcat:Distribution ;
    dct:issued "2022-01-25T19:25:53.776347"^^xsd:dateTime ;
    dct:modified "2025-11-21T18:18:13.199581"^^xsd:dateTime ;
    dct:title "Web Resource" ;
    dcat:accessURL <http://dx.doi.org/10.1029/2019WR024922> .

<https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/e3024286-9836-45f0-b18d-b5f99d6f756f> a dcat:Distribution ;
    dct:description "The metadata original source" ;
    dct:format "XML" ;
    dct:issued "2022-01-25T19:25:53.776355"^^xsd:dateTime ;
    dct:modified "2025-11-21T18:18:13.200707"^^xsd:dateTime ;
    dct:title "Original Metadata" ;
    dcat:accessURL <https://data.doi.gov/harvest/object/130f418c-9682-4563-bfa4-d19cd97e82f4> ;
    dcat:mediaType "text/xml" .

<https://data.amerigeoss.org/dataset/542a547c-7c2f-4762-81ee-8ac7854d52da/resource/e4defd86-2a38-41eb-9296-add4f11111c8> a dcat:Distribution ;
    dct:issued "2022-01-25T19:25:53.776352"^^xsd:dateTime ;
    dct:modified "2025-11-21T18:18:13.200337"^^xsd:dateTime ;
    dct:title "Web Resource" ;
    dcat:accessURL <https://doi.org/10.5194/gmd-12-473-2019> .

<https://data.amerigeoss.org/organization/727dbdd5-3f98-4ac0-9d28-5e344558139b> a foaf:Agent ;
    foaf:name "US Migrating" .