@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/3d648610-52fe-447f-845d-f35fbc60f1a9> 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 "6015582d-4602-4f90-aeb7-0aed108f9721" ;
    dct:issued "2025-11-21T03:31:27.301837"^^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/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/0bce6cf9-2595-48c2-b021-847570148dd2>,
        <https://data.amerigeoss.org/dataset/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/15fa42d7-504c-4c15-a7b7-46ac0dce027b>,
        <https://data.amerigeoss.org/dataset/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/42e10b8a-7010-4f69-b710-9eb56c184358>,
        <https://data.amerigeoss.org/dataset/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/75d4db98-ac3a-4bcc-827d-77f9ffd85841>,
        <https://data.amerigeoss.org/dataset/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/9cc3fc31-fef5-44a0-9f0a-51cd214a2d63>,
        <https://data.amerigeoss.org/dataset/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/bf2974d2-8f62-4897-ad96-91313c7e12b8> ;
    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/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/0bce6cf9-2595-48c2-b021-847570148dd2> a dcat:Distribution ;
    dct:description "The metadata original source" ;
    dct:format "XML" ;
    dct:issued "2022-08-07T11:44:35.720106"^^xsd:dateTime ;
    dct:modified "2025-11-21T03:31:27.290573"^^xsd:dateTime ;
    dct:title "Original Metadata" ;
    dcat:accessURL <https://data.doi.gov/harvest/object/2e51be34-c76d-43d8-b682-deb699c84aeb> ;
    dcat:mediaType "text/xml" .

<https://data.amerigeoss.org/dataset/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/15fa42d7-504c-4c15-a7b7-46ac0dce027b> a dcat:Distribution ;
    dct:description "CSDGM IMPORT ERROR: No digtinfo/formcont" ;
    dct:issued "2022-08-07T11:44:35.720085"^^xsd:dateTime ;
    dct:modified "2025-11-21T03:31:27.288576"^^xsd:dateTime ;
    dct:title "two comma separated text files" ;
    dcat:accessURL <http://dx.doi.org/10.5066/P9AQPIVD> .

<https://data.amerigeoss.org/dataset/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/42e10b8a-7010-4f69-b710-9eb56c184358> a dcat:Distribution ;
    dct:issued "2022-08-07T11:44:35.720095"^^xsd:dateTime ;
    dct:modified "2025-11-21T03:31:27.289398"^^xsd:dateTime ;
    dct:title "Web Resource" ;
    dcat:accessURL <http://dx.doi.org/10.1029/2019WR024922> .

<https://data.amerigeoss.org/dataset/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/75d4db98-ac3a-4bcc-827d-77f9ffd85841> a dcat:Distribution ;
    dct:issued "2022-08-07T11:44:35.720099"^^xsd:dateTime ;
    dct:modified "2025-11-21T03:31:27.289797"^^xsd:dateTime ;
    dct:title "Web Resource" ;
    dcat:accessURL <http://dx.doi.org/10.1029/2003JD003823> .

<https://data.amerigeoss.org/dataset/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/9cc3fc31-fef5-44a0-9f0a-51cd214a2d63> a dcat:Distribution ;
    dct:issued "2022-08-07T11:44:35.720102"^^xsd:dateTime ;
    dct:modified "2025-11-21T03:31:27.290197"^^xsd:dateTime ;
    dct:title "Web Resource" ;
    dcat:accessURL <https://doi.org/10.5194/gmd-12-473-2019> .

<https://data.amerigeoss.org/dataset/3d648610-52fe-447f-845d-f35fbc60f1a9/resource/bf2974d2-8f62-4897-ad96-91313c7e12b8> a dcat:Distribution ;
    dct:issued "2022-08-07T11:44:35.720091"^^xsd:dateTime ;
    dct:modified "2025-11-21T03:31:27.288990"^^xsd:dateTime ;
    dct:title "Web Resource" ;
    dcat:accessURL <http://dx.doi.org/10.5066/P9AQPIVD> .

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