@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/7a1d02d3-4423-4df2-8316-5f56f635870e> a dcat:Dataset ;
    dct:description "Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models were configured and calibrated with training data to reduce root-mean squared error. Uncalibrated models used default configurations (PB0; see Winslow et al. 2016 for details) and no parameters were adjusted according to model fit with observations. Deep Learning (DL) models were Long Short-Term Memory artificial recurrent neural network models which used training data to adjust model structure and weights for temperature predictions (Jia et al. 2019). Process-Guided Deep Learning (PGDL) models were DL models with an added physical constraint for energy conservation as a loss term. These models were pre-trained with uncalibrated Process-Based model outputs (PB0) before training on actual temperature observations." ;
    dct:identifier "88a65dd3-581d-4126-b966-a29a85f2769f" ;
    dct:issued "2025-11-22T20:39:06.026887"^^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: 5a Lake Mendota detailed prediction data" ;
    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/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/0ba7f62d-8314-4dea-8288-dab00036fb72>,
        <https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/376e65cd-e08a-4c7b-8ce2-3d99d0c14b85>,
        <https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/78cca18d-70cf-4b32-a609-02f5068bda11>,
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        <https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/92637ce0-dbca-4105-b977-73adb7b6b50f>,
        <https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/946bc073-f809-4259-976a-1a5b83a92ca4>,
        <https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/d06362c4-e4f9-431e-9e15-6e0c8804b09d>,
        <https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/e4544ecc-8f57-4e0b-a95e-8b1efa8bafca> ;
    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-5d915cb2e4b0c4f70d0ce523",
        "water" ;
    dcat:theme <%7Bgeospatial%7D> .

<https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/0ba7f62d-8314-4dea-8288-dab00036fb72> a dcat:Distribution ;
    dct:issued "2022-01-25T19:25:14.428980"^^xsd:dateTime ;
    dct:modified "2025-11-22T20:39:06.013115"^^xsd:dateTime ;
    dct:title "Web Resource" ;
    dcat:accessURL <http://dx.doi.org/10.1029/2019WR024922> .

<https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/376e65cd-e08a-4c7b-8ce2-3d99d0c14b85> a dcat:Distribution ;
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    dct:title "Web Resource" ;
    dcat:accessURL <http://dx.doi.org/10.5066/F7DV1H10> .

<https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/78cca18d-70cf-4b32-a609-02f5068bda11> a dcat:Distribution ;
    dct:description "1810.02880.pdf" ;
    dct:format "PDF" ;
    dct:issued "2022-01-25T19:25:14.428995"^^xsd:dateTime ;
    dct:modified "2025-11-22T20:39:06.014379"^^xsd:dateTime ;
    dct:title "PDF File" ;
    dcat:accessURL <https://arxiv.org/pdf/1810.02880.pdf> .

<https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/87ca1ede-7c2f-4ae4-a349-64f6bba59636> a dcat:Distribution ;
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    dct:modified "2025-11-22T20:39:06.013537"^^xsd:dateTime ;
    dct:title "Web Resource" ;
    dcat:accessURL <https://doi.org/10.5194/gmd-12-473-2019> .

<https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/92637ce0-dbca-4105-b977-73adb7b6b50f> a dcat:Distribution ;
    dct:description "CSDGM IMPORT ERROR: No digtinfo/formcont" ;
    dct:issued "2022-01-25T19:25:14.428963"^^xsd:dateTime ;
    dct:modified "2025-11-22T20:39:06.012246"^^xsd:dateTime ;
    dct:title "Ten comma-separated files" ;
    dcat:accessURL <http://dx.doi.org/10.5066/P9AQPIVD> .

<https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/946bc073-f809-4259-976a-1a5b83a92ca4> a dcat:Distribution ;
    dct:issued "2022-01-25T19:25:14.428974"^^xsd:dateTime ;
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    dct:title "Web Resource" ;
    dcat:accessURL <http://dx.doi.org/10.5066/P9AQPIVD> .

<https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/d06362c4-e4f9-431e-9e15-6e0c8804b09d> a dcat:Distribution ;
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    dct:title "Web Resource" ;
    dcat:accessURL <https://doi.org/10.5066/F7D798MJ> .

<https://data.amerigeoss.org/dataset/7a1d02d3-4423-4df2-8316-5f56f635870e/resource/e4544ecc-8f57-4e0b-a95e-8b1efa8bafca> a dcat:Distribution ;
    dct:description "The metadata original source" ;
    dct:format "XML" ;
    dct:issued "2022-01-25T19:25:14.429004"^^xsd:dateTime ;
    dct:modified "2025-11-22T20:39:06.015179"^^xsd:dateTime ;
    dct:title "Original Metadata" ;
    dcat:accessURL <https://data.doi.gov/harvest/object/c28b3df0-5537-4e37-96a1-82b472380adc> ;
    dcat:mediaType "text/xml" .

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