Item talk:Q323224

{

 "id": "10.5066/p9zr7bwl",
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       "name": "Larson, Danelle M",
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       "name": "Stockdill, Alaina",
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         "University of Wisconsin La Crosse"
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       "name": "McKean, Casey",
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       "name": "Davis, Killian",
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         "University of Wisconsin La Crosse"
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       "name": "Erickson, Richard A",
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       "name": "Hlavacek, Enrika J",
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   ],
   "titles": [
     {
       "title": "Dataset from the Upper Mississippi River Restoration Program (1993-2019) to reconstruct missing data by comparing interpolation techniques"
     }
   ],
   "publisher": "U.S. Geological Survey",
   "container": {},
   "publicationYear": 2023,
   "subjects": [
     {
       "subject": "Information Sciences, Water Resources"
     }
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   "contributors": [],
   "dates": [
     {
       "date": "2023",
       "dateType": "Issued"
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     {
       "description": "The dataset accompanies the scientific article, \"Reconstructing missing data by comparing interpolation techniques: applications for long-term water quality data.\" Missingness is typical in large datasets, but intercomparisons of interpolation methods can alleviate data gaps and common problems associated with missing data. We compared seven popular interpolation methods for predicting missing values in a long-term water quality data set from the upper Mississippi River, USA.",
       "descriptionType": "Abstract"
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   "created": "2023-05-09T16:17:19Z",
   "registered": "2023-05-09T16:17:19Z",
   "published": null,
   "updated": "2023-08-21T08:55:12Z"
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