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{
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{
            
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  "Creator": "Creator",
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  "Creator": "Creator",
            
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  "Date": "2019-08-09",
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  "Date": "2019-08-09",
            
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  "IdentifierType": "DOI",
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  "IdentifierType": "DOI",
            
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  "PublicationYear": "2022",
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  "PublicationYear": "2022",
            
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  "Publisher": "CanWIN",
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  "Publisher": "CanWIN",
            
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  "RelatedIdentifierType": "URL",
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  "RelatedIdentifierType": "URL",
            
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  "RelationType": "IsSupplementTo",
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  "RelationType": "IsSupplementTo",
            
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  "ResourceType": "imagery",
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  "ResourceType": "imagery",
            
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  "Rights": "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 
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  "Rights": "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 
            
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International",
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International",
            
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  "Version": "1.0",
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  "Version": "1.0",
            
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  "accessTerms": "CanWIN datasets are licensed individually, however 
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  "accessTerms": "CanWIN datasets are licensed individually, however 
            
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most are licensed under the Creative Commons Attribution 4.0 
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most are licensed under the Creative Commons Attribution 4.0 
            
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International (CC BY 4.0) Public License. Details for the licence 
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International (CC BY 4.0) Public License. Details for the licence 
            
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applied can be found using the Licence URL link provided with each 
16
applied can be found using the Licence URL link provided with each 
            
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dataset. \r\nBy using data and information provided on this site you 
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dataset. \r\nBy using data and information provided on this site you 
            
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accept the terms and conditions of the License. Unless otherwise 
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accept the terms and conditions of the License. Unless otherwise 
            
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specified, the license grants the rights to the public to use and 
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specified, the license grants the rights to the public to use and 
            
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share the data and results derived therefrom as long as the proper 
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share the data and results derived therefrom as long as the proper 
            
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acknowledgment is given to the data licensor (citation), that any 
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acknowledgment is given to the data licensor (citation), that any 
            
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alteration to the data is clearly indicated, and that a link to the 
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alteration to the data is clearly indicated, and that a link to the 
            
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original data and the license is made available.",
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original data and the license is made available.",
            
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  "activityCollectionType": "Field Measurement",
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  "activityCollectionType": "Field Measurement",
            
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  "analyticalMethodName": "",
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  "analyticalMethodName": "",
            
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  "author": null,
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  "author": null,
            
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  "author_email": null,
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  "author_email": null,
            
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  "campaignEndDate": "2019-08-09",
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  "campaignEndDate": "2019-08-09",
            
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  "campaignStartDate": "2019-07-28",
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  "campaignStartDate": "2019-07-28",
            
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  "comments": "",
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  "comments": "",
            
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  "contributorName": "Chan, Wayne",
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  "contributorName": "Chan, Wayne",
            
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  "contributorType": "DataCurator",
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  "contributorType": "DataCurator",
            
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  "contributors": [
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  "contributors": [
            
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    {
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    {
            
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      "affiliation": "Centre for Earth Observation Science - 
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      "affiliation": "Centre for Earth Observation Science - 
            
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University of Manitoba",
36
University of Manitoba",
            
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      "contributorName": "Harasyn, Madison",
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      "contributorName": "Harasyn, Madison",
            
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      "contributorType": "DataCollector",
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      "contributorType": "DataCollector",
            
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      "email": "Madison.harasyn@umanitoba.ca",
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      "email": "Madison.harasyn@umanitoba.ca",
            
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      "nameIdentifier": "https://orcid.org/0000-0002-5741-6766",
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      "nameIdentifier": "https://orcid.org/0000-0002-5741-6766",
            
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      "nameIdentifierScheme": "ORCID",
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      "nameIdentifierScheme": "ORCID",
            
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      "schemeURI": "http://orcid.org/"
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      "schemeURI": "http://orcid.org/"
            
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    },
            
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    {
            
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      "affiliation": "Centre for Earth Observation Science - 
            
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University of Manitoba",
            
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      "contributorName": "Chan, Wayne",
            
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      "contributorType": "Researcher",
            
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      "email": "wayne.chan@umanitoba.ca",
            
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      "nameIdentifier": ""
            
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    }
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    }
            
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  ],
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  ],
            
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  "creatorName": [
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  "creatorName": [
            
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    {
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    {
            
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      "author": "Barber, David",
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      "author": "Barber, David",
            
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      "creatorAffiliation": "Centre for Earth Observation Science - 
56
      "creatorAffiliation": "Centre for Earth Observation Science - 
            
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University of Manitoba",
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University of Manitoba",
            
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      "creatorEmail": "david.barber@umanitoba.ca",
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      "creatorEmail": "david.barber@umanitoba.ca",
            
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      "creatorNameIdentifier": "",
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      "creatorNameIdentifier": "",
            
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      "nameType": "Personal"
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      "nameType": "Personal"
            
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    }
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    }
            
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  ],
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  ],
            
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  "creator_user_id": "cde7b848-a882-4fc7-97c9-670417bd6b43",
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  "creator_user_id": "cde7b848-a882-4fc7-97c9-670417bd6b43",
            
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  "dataCuratorAffiliation": "Centre for Earth Observation Science - 
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  "dataCuratorAffiliation": "Centre for Earth Observation Science - 
            
57
University of Manitoba",
65
University of Manitoba",
            
58
  "dataCuratorEmail": "wayne.chan@umanitoba.ca",
66
  "dataCuratorEmail": "wayne.chan@umanitoba.ca",
            
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  "datasetCitation": "Harasyn, Madison; Barber, David, May 2021, 
67
  "datasetCitation": "Harasyn, Madison; Barber, David, May 2021, 
            
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\u201c2019 Churchill UAV Data\u201d, (N/A)",
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\u201c2019 Churchill UAV Data\u201d, (N/A)",
            
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  "datasetLevel": "1.1",
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  "datasetLevel": "1.1",
            
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  "datasetPublisher": "CanWIN",
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  "datasetPublisher": "CanWIN",
            
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  "dateType": "Updated",
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  "dateType": "Updated",
            
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  "descriptionType": "Abstract",
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  "descriptionType": "Abstract",
            
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  "eastBoundLongitude": "-94.0706395086",
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  "eastBoundLongitude": "-94.0706395086",
            
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  "embargoDate": "",
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  "embargoDate": "",
            
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  "endDate": "2019-08-09",
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  "endDate": "2019-08-09",
            
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  "endDateType": "Other",
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  "endDateType": "Other",
            
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  "frequency": "Not planned",
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  "frequency": "Not planned",
            
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  "funderIdentifierType": "",
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  "funderIdentifierType": "",
            
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  "funderName": "",
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  "funderName": "",
            
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  "funderSchemeURI": "",
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  "funderSchemeURI": "",
            
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  "groups": [
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  "groups": [
            
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    {
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    {
            
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      "description": "Inland water features, drainage systems and 
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      "description": "Image: \"Earth from Space\" by NASA Goddard 
            
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their characteristics. Examples of data you can find here include 
84
Photo and Video is licensed under CC BY 2.0",
            
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river and lake data, water quality data. \r\n\r\nIn CEOS, related 

            
78
research themes include biogeochemistry, Inland lakes and waters, 

            
79
modelling, remote sensing and technology, trace metals and 

            
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contaminants.",

            
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      "display_name": "Freshwater",
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      "display_name": "Remote Sensing",
            
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      "id": "8f8cd877-b037-4b1a-b928-f86d9e093741",
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      "id": "3ec49cbb-4da6-4fe8-8d54-5b6ce03b49d9",
            
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      "image_display_url": 
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      "image_display_url": 
            
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/data/uploads/group/2021-10-31-211937.658599hyinspirehydrography.svg",
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anitoba.ca/data/uploads/group/2022-02-05-222621.346712earthimage.jpg",
            
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      "name": "freshwater",
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      "name": "remote-sensing",
            
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      "title": "Freshwater"
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      "title": "Remote Sensing"
            
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    },

            
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    {

            
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      "description": "Features and characteristics of salt water 

            
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bodies.\r\n\r\nIn CEOS, related research themes include 

            
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biogeochemistry, modelling, marine mammals, oil spill response, 

            
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physical oceanography, remote sensing and technology and trace metals 

            
93
and contaminants",

            
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      "display_name": "Marine",

            
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      "id": "98238b1c-5be8-41ad-8c6e-74cdc4f5f369",

            
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      "image_display_url": 

            
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ata/uploads/group/2021-10-31-211516.365746ofinspireoceanographic.svg",

            
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      "name": "marine",

            
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      "title": "Marine"

            
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    }
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    }
            
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  ],
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  ],
            
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  "id": "b5f259b4-3ace-4750-bfb0-47c4e794082f",
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  "id": "b5f259b4-3ace-4750-bfb0-47c4e794082f",
            
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  "isopen": false,
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  "isopen": false,
            
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  "keywords": "Churchill estuary,UAV,aerial 
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  "keywords": "Churchill estuary,UAV,aerial 
            
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photos,beluga,boat,kayak,video",
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photos,beluga,boat,kayak,video",
            
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  "kvSchemeURI": "",
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  "kvSchemeURI": "",
            
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  "laboratory": "CEOS",
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  "laboratory": "CEOS",
            
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  "licenceShemeURI": "https://spdx.org/licenses",
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  "licenceShemeURI": "https://spdx.org/licenses",
            
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  "licenceType": "Open",
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  "licenceType": "Open",
            
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  "license_id": null,
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  "license_id": null,
            
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  "license_title": null,
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  "license_title": null,
            
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  "maintainer": null,
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  "maintainer": null,
            
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  "maintainer_email": null,
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  "maintainer_email": null,
            
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  "metadata_created": "2022-02-04T19:17:36.940301",
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  "metadata_created": "2022-02-04T19:17:36.940301",
            
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  "metadata_modified": "2022-02-14T16:39:47.574630",
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  "metadata_modified": "2022-02-14T17:02:48.659072",
            
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  "methodCitation": "",
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  "methodCitation": "",
            
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  "methodDescrioption": "",
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  "methodDescrioption": "",
            
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  "methodDescriptionType": "Methods",
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  "methodDescriptionType": "Methods",
            
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  "methodLink": "",
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  "methodLink": "",
            
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  "methodSummary": "",
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  "methodSummary": "",
            
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  "methodUrl": "",
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  "methodUrl": "",
            
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  "name": "churchill-beluga-boat-drone-imagery",
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  "name": "churchill-beluga-boat-drone-imagery",
            
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  "northBoundLatitude": "58.8195795207",
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  "northBoundLatitude": "58.8195795207",
            
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  "notes": "Aerial imagery surveys are commonly used in marine mammal 
115
  "notes": "Aerial imagery surveys are commonly used in marine mammal 
            
125
research to determine population size, habitat distribution and 
116
research to determine population size, habitat distribution and 
            
126
habitat use. Analysis of aerial photos involves hours of manually 
117
habitat use. Analysis of aerial photos involves hours of manually 
            
127
identifying individuals present in each image and converting raw 
118
identifying individuals present in each image and converting raw 
            
128
counts into useable biological statistics. Our research proposes the 
119
counts into useable biological statistics. Our research proposes the 
            
129
use of deep learning algorithms as an assistive technology to increase 
120
use of deep learning algorithms as an assistive technology to increase 
            
130
the efficiency of the marine mammal research workflow. To test the 
121
the efficiency of the marine mammal research workflow. To test the 
            
131
feasibility of this proposal, the existing YOLOv4 convolutional neural 
122
feasibility of this proposal, the existing YOLOv4 convolutional neural 
            
132
network model was trained to detect belugas, kayaks and motorized 
123
network model was trained to detect belugas, kayaks and motorized 
            
133
boats in unmanned aerial vehicle (UAV) imagery. Computer-based object 
124
boats in unmanned aerial vehicle (UAV) imagery. Computer-based object 
            
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detection achieved an average precision of 61.17% for belugas, 98.58% 
125
detection achieved an average precision of 61.17% for belugas, 98.58% 
            
135
for boats, and 95.97% for kayaks. We then tested the performance of 
126
for boats, and 95.97% for kayaks. We then tested the performance of 
            
136
computer vision tracking of belugas and manned watercraft in UAV 
127
computer vision tracking of belugas and manned watercraft in UAV 
            
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videos using the DeepSORT tracking algorithm, achieving a multiple 
128
videos using the DeepSORT tracking algorithm, achieving a multiple 
            
138
object tracking accuracy (MOTA) ranging from 37% \u2013 88% and 
129
object tracking accuracy (MOTA) ranging from 37% \u2013 88% and 
            
139
multiple object tracking precision (MOTP) between 63% \u2013 86%. 
130
multiple object tracking precision (MOTP) between 63% \u2013 86%. 
            
140
Results from this research indicate that deep learning technology can 
131
Results from this research indicate that deep learning technology can 
            
141
perform at a similar caliber as human annotators in beluga and 
132
perform at a similar caliber as human annotators in beluga and 
            
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watercraft detection and tracking, allowing for larger datasets to be 
133
watercraft detection and tracking, allowing for larger datasets to be 
            
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processed within a fraction of the time. ",
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processed within a fraction of the time. ",
            
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  "num_resources": 17,
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  "num_resources": 17,
            
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  "num_tags": 7,
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  "num_tags": 7,
            
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  "organization": {
137
  "organization": {
            
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    "approval_status": "approved",
138
    "approval_status": "approved",
            
148
    "created": "2017-07-21T13:15:49.935872",
139
    "created": "2017-07-21T13:15:49.935872",
            
149
    "description": "The Centre for Earth Observation Science (CEOS) 
140
    "description": "The Centre for Earth Observation Science (CEOS) 
            
150
was established in 1994 with a mandate to research, preserve and 
141
was established in 1994 with a mandate to research, preserve and 
            
151
communicate knowledge of Earth system processes using the technologies 
142
communicate knowledge of Earth system processes using the technologies 
            
152
of Earth Observation Science. Research is multidisciplinary and 
143
of Earth Observation Science. Research is multidisciplinary and 
            
153
collaborative seeking to understand the complex interrelationships 
144
collaborative seeking to understand the complex interrelationships 
            
154
between elements of Earth systems, and how these systems will likely 
145
between elements of Earth systems, and how these systems will likely 
            
155
respond to climate change. Although researchers have worked in many 
146
respond to climate change. Although researchers have worked in many 
            
156
regions, the Arctic marine system has always been a unifying focus of 
147
regions, the Arctic marine system has always been a unifying focus of 
            
157
activity.\r\n\r\nIn 2012, CEOS, along with the Greenland Climate 
148
activity.\r\n\r\nIn 2012, CEOS, along with the Greenland Climate 
            
158
Research Centre (GCRC, Nuuk, Greenland) and the Arctic Research Centre 
149
Research Centre (GCRC, Nuuk, Greenland) and the Arctic Research Centre 
            
159
(ARC, Aarhus, Denmark) established the Arctic Science Partnership, 
150
(ARC, Aarhus, Denmark) established the Arctic Science Partnership, 
            
160
thereby integrating academic and research initiatives.\r\n\r\nAreas of 
151
thereby integrating academic and research initiatives.\r\n\r\nAreas of 
            
161
existing research activity are divided among key themes:\r\n\r\nArctic 
152
existing research activity are divided among key themes:\r\n\r\nArctic 
            
162
Anthropology/Paleoclimatology: LiDAR scanning and digital site 
153
Anthropology/Paleoclimatology: LiDAR scanning and digital site 
            
163
preservation, archaeo-geophysics, permafrost degredation, lithic 
154
preservation, archaeo-geophysics, permafrost degredation, lithic 
            
164
morphometrics, zooarchaeology, proxy studies, paleodistribution of sea 
155
morphometrics, zooarchaeology, proxy studies, paleodistribution of sea 
            
165
ice, landscape learning, Paleo-Eskimo culture, Thule Inuit culture, 
156
ice, landscape learning, Paleo-Eskimo culture, Thule Inuit culture, 
            
166
ethnographic analogy, traditional knowledge, climate change and 
157
ethnographic analogy, traditional knowledge, climate change and 
            
167
northern heritage resource management.\r\n\r\nAtmospheric 
158
northern heritage resource management.\r\n\r\nAtmospheric 
            
168
Studies/Meteorology: Boundary layer, precipitation, clouds, storms and 
159
Studies/Meteorology: Boundary layer, precipitation, clouds, storms and 
            
169
extreme weather, circulation, eddy correlations, polar vortex, 
160
extreme weather, circulation, eddy correlations, polar vortex, 
            
170
climate, teleconnections, geophysical fluid dynamics, flux and energy 
161
climate, teleconnections, geophysical fluid dynamics, flux and energy 
            
171
budgets, ocean-sea ice-atmosphere interface, radiative transfer, ice 
162
budgets, ocean-sea ice-atmosphere interface, radiative transfer, ice 
            
172
albedo feedback, cloud radiative forcing, pCO2. 
163
albedo feedback, cloud radiative forcing, pCO2. 
            
173
\r\n\r\nBiogeochemistry: Organic carbon, greenhouse gases, bubbles, 
164
\r\n\r\nBiogeochemistry: Organic carbon, greenhouse gases, bubbles, 
            
174
Ikaite, carbonate chemistry, CO2 fluxes, mercury and other trace 
165
Ikaite, carbonate chemistry, CO2 fluxes, mercury and other trace 
            
175
metals, minerals, hydrocarbons, brine processes, otolith 
166
metals, minerals, hydrocarbons, brine processes, otolith 
            
176
microchemistry, sediments, biomarkers. \r\n\r\nContaminants: Mercury, 
167
microchemistry, sediments, biomarkers. \r\n\r\nContaminants: Mercury, 
            
177
trace metals, PAHs, source, transport, transformation, pathways, 
168
trace metals, PAHs, source, transport, transformation, pathways, 
            
178
bioaccumulations, marine ecosystems, marine chemistry. \r\nEarth 
169
bioaccumulations, marine ecosystems, marine chemistry. \r\nEarth 
            
179
Observation Science: Active and passive microwave, LiDAR, EM 
170
Observation Science: Active and passive microwave, LiDAR, EM 
            
180
induction, spatial-temporal analysis, forward and inverse scattering 
171
induction, spatial-temporal analysis, forward and inverse scattering 
            
181
models, complex permittivity, ocean colour, ocean surface roughness, 
172
models, complex permittivity, ocean colour, ocean surface roughness, 
            
182
NIR, TIR, satellite telemetry, GPS. Ice-Associated Biology: 
173
NIR, TIR, satellite telemetry, GPS. Ice-Associated Biology: 
            
183
Biophysical processes, primary production; ice algae, ice 
174
Biophysical processes, primary production; ice algae, ice 
            
184
microbiology, bio-optics, under-ice phytoplankton. \r\n\r\nInland 
175
microbiology, bio-optics, under-ice phytoplankton. \r\n\r\nInland 
            
185
Lakes and Waters: Hydrologic connectivity, watershed systems, sediment 
176
Lakes and Waters: Hydrologic connectivity, watershed systems, sediment 
            
186
transport, nutrient transport, contaminants, landscape processes, 
177
transport, nutrient transport, contaminants, landscape processes, 
            
187
remote sensing, freshwater-marine coupling. Marine Mammals: Seals, 
178
remote sensing, freshwater-marine coupling. Marine Mammals: Seals, 
            
188
whales, habitat, conservation, satellite telemetry, distribution, 
179
whales, habitat, conservation, satellite telemetry, distribution, 
            
189
population studies, prey behaviour, bioacoustics.\r\n\r\nModelling: 
180
population studies, prey behaviour, bioacoustics.\r\n\r\nModelling: 
            
190
Simulation of sea ice and oceanic regional processes, Nucleus for 
181
Simulation of sea ice and oceanic regional processes, Nucleus for 
            
191
European Modelling of the Ocean (NEMO), ice-ocean modelling and 
182
European Modelling of the Ocean (NEMO), ice-ocean modelling and 
            
192
interactions, hind cast simulations and projections for sea ice state 
183
interactions, hind cast simulations and projections for sea ice state 
            
193
and ocean variables based on CMIP5 scenarios and MIROC5 forcing, 
184
and ocean variables based on CMIP5 scenarios and MIROC5 forcing, 
            
194
validation.\r\n\r\nOceanography: Circulation, temperature, in-flow and 
185
validation.\r\n\r\nOceanography: Circulation, temperature, in-flow and 
            
195
out-flow shelves, water dynamics, microturbulence, Beaufort Gyre, eddy 
186
out-flow shelves, water dynamics, microturbulence, Beaufort Gyre, eddy 
            
196
correlations.\r\n\r\nSea Ice Geophysics:Thermodynamic and dynamic 
187
correlations.\r\n\r\nSea Ice Geophysics:Thermodynamic and dynamic 
            
197
processes, extreme ice features and hazards, snow, ridges, 
188
processes, extreme ice features and hazards, snow, ridges, 
            
198
polynyas.\r\n\r\nTraditional and Local Knowledge: Indigenous cultures, 
189
polynyas.\r\n\r\nTraditional and Local Knowledge: Indigenous cultures, 
            
199
Inuit, Inuvialuit, oral history, toponomy, mobility and settlement, 
190
Inuit, Inuvialuit, oral history, toponomy, mobility and settlement, 
            
200
hunting, food security, sea ice use, community-based research, 
191
hunting, food security, sea ice use, community-based research, 
            
201
community-based monitoring, two ways of knowing.",
192
community-based monitoring, two ways of knowing.",
            
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    "title": "CEOS",
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    "title": "CEOS",
            
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      "description": "Researchers at CEOS are often asked to write a 
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      "description": "Researchers at CEOS are often asked to write a 
            
230
field story about their work, to make their research more accessible. 
221
field story about their work, to make their research more accessible. 
            
231
We decided to do something a little different for our work on applying 
222
We decided to do something a little different for our work on applying 
            
232
machine learning to detecting and tracking beluga whales: we are 
223
machine learning to detecting and tracking beluga whales: we are 
            
233
presenting it as a comic-book style video!\r\n\r\nComics and graphic 
224
presenting it as a comic-book style video!\r\n\r\nComics and graphic 
            
234
novels are a very popular genre now and cover a wide range of 
225
novels are a very popular genre now and cover a wide range of 
            
235
subjects, from traditional 
226
subjects, from traditional 
            
236
superheroes](https://en.wikipedia.org/wiki/Batman:_The_Long_Halloween) 
227
superheroes](https://en.wikipedia.org/wiki/Batman:_The_Long_Halloween) 
            
237
to historical figures like [Louis 
228
to historical figures like [Louis 
            
238
Riel](https://en.wikipedia.org/wiki/Louis_Riel_comics). They have also 
229
Riel](https://en.wikipedia.org/wiki/Louis_Riel_comics). They have also 
            
239
become a novel and emerging way of communicating science. There are 
230
become a novel and emerging way of communicating science. There are 
            
240
graphic novels about 
231
graphic novels about 
            
241
ooks/303/303922/mysteries-of-the-quantum-universe/9780141985176.html), 
232
ooks/303/303922/mysteries-of-the-quantum-universe/9780141985176.html), 
            
242
//www.larrygonick.com/titles/science/the-cartoon-guide-to-chemistry/), 
233
//www.larrygonick.com/titles/science/the-cartoon-guide-to-chemistry/), 
            
243
biology](https://us.macmillan.com/books/9780809089475/thestuffoflife), 
234
biology](https://us.macmillan.com/books/9780809089475/thestuffoflife), 
            
244
and [math](https://en.wikipedia.org/wiki/Logicomix), and ones about 
235
and [math](https://en.wikipedia.org/wiki/Logicomix), and ones about 
            
245
famous scientists, such as [Stephen 
236
famous scientists, such as [Stephen 
            
246
Hawking](https://us.macmillan.com/books/9781626720251/hawking) and 
237
Hawking](https://us.macmillan.com/books/9781626720251/hawking) and 
            
247
[Alan 
238
[Alan 
            
248
g](https://www.abramsbooks.com/product/imitation-game_9781419718939/). 
239
g](https://www.abramsbooks.com/product/imitation-game_9781419718939/). 
            
249
Comics are not only used for science education, however; they are also 
240
Comics are not only used for science education, however; they are also 
            
250
gaining popularity as a means of disseminating new research findings. 
241
gaining popularity as a means of disseminating new research findings. 
            
251
The European Research Council (ERC), for example, recently decided to 
242
The European Research Council (ERC), for example, recently decided to 
            
252
create [comic-book adaptations](https://www.erccomics.com/) of some of 
243
create [comic-book adaptations](https://www.erccomics.com/) of some of 
            
253
their funded projects, as an innovative way to showcase 
244
their funded projects, as an innovative way to showcase 
            
254
them.\r\n\r\nThe process of doing scientific research is very visual, 
245
them.\r\n\r\nThe process of doing scientific research is very visual, 
            
255
with researchers often drawing out ideas on a whiteboard or on paper. 
246
with researchers often drawing out ideas on a whiteboard or on paper. 
            
256
Yet, the end product is usually an academic journal article that is 
247
Yet, the end product is usually an academic journal article that is 
            
257
mostly text and a few graphs, couched in technical language and 
248
mostly text and a few graphs, couched in technical language and 
            
258
presented in a formalized structure. \r\n\r\nComics and graphic novels 
249
presented in a formalized structure. \r\n\r\nComics and graphic novels 
            
259
can bridge this gap between the textual and visual by combining a 
250
can bridge this gap between the textual and visual by combining a 
            
260
narrative structure with visual storytelling to bring a story to life. 
251
narrative structure with visual storytelling to bring a story to life. 
            
261
And since comics appeal to people of all ages and cultural 
252
And since comics appeal to people of all ages and cultural 
            
262
backgrounds, they can engage new groups of people, rather than the 
253
backgrounds, they can engage new groups of people, rather than the 
            
263
audiences who typically read research literature. \r\n\r\nJournal 
254
audiences who typically read research literature. \r\n\r\nJournal 
            
264
articles can also wrongly give the impression that the research was a 
255
articles can also wrongly give the impression that the research was a 
            
265
straightforward \"royal road\" from hypothesis to conclusion, which is 
256
straightforward \"royal road\" from hypothesis to conclusion, which is 
            
266
seldom the case. The false paths and dead-ends that were explored and 
257
seldom the case. The false paths and dead-ends that were explored and 
            
267
the obstacles that were encountered are never mentioned. Much like a 
258
the obstacles that were encountered are never mentioned. Much like a 
            
268
finished building, the scaffolding has been removed, leaving only the 
259
finished building, the scaffolding has been removed, leaving only the 
            
269
final result for people to see. Learning about these dead-ends, 
260
final result for people to see. Learning about these dead-ends, 
            
270
however, can be instructive and reassuring to a student starting out 
261
however, can be instructive and reassuring to a student starting out 
            
271
in research. A comic can show this type of behind-the-scenes work that 
262
in research. A comic can show this type of behind-the-scenes work that 
            
272
is rarely discussed in a more formal article.\r\n\r\nWe hope that our 
263
is rarely discussed in a more formal article.\r\n\r\nWe hope that our 
            
273
comic-book video illustrates the research process, with its ups and 
264
comic-book video illustrates the research process, with its ups and 
            
274
downs, and also shows how people with different backgrounds work 
265
downs, and also shows how people with different backgrounds work 
            
275
together on a project. If it motivates people to find out more about 
266
together on a project. If it motivates people to find out more about 
            
276
our work (and read the dry, academic version of it), that's all we can 
267
our work (and read the dry, academic version of it), that's all we can 
            
277
ask for!\r\nWithout further ado!",
268
ask for!\r\nWithout further ado!",
            
278
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      "created": "2022-02-09T19:57:51.773988",
            
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      "datastore_contains_all_records_of_source_file": false,
            
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      "description": "CANWIN metadata templates are filled out for 
684
      "description": "CANWIN metadata templates are filled out for 
            
694
instruments, deployments, datasets, and projects. This template is for 
685
instruments, deployments, datasets, and projects. This template is for 
            
695
UAV (unmanned aerial vehicle) videos and photos collected during the 
686
UAV (unmanned aerial vehicle) videos and photos collected during the 
            
696
2019 field season over the Churchill Estuary.",
687
2019 field season over the Churchill Estuary.",
            
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      "format": "DOCX",
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      "format": "DOCX",
            
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      "hash": "",
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      "hash": "",
            
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      "id": "e07866e4-6be1-4720-94f1-5cd27e056e05",
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      "id": "e07866e4-6be1-4720-94f1-5cd27e056e05",
            
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      "last_modified": "2022-02-09T19:57:51.663259",
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      "last_modified": "2022-02-09T19:57:51.663259",
            
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      "metadata_modified": "2022-02-10T16:11:27.431362",
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      "metadata_modified": "2022-02-10T16:11:27.431362",
            
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      "mimetype_inner": null,
            
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      "name": "CANWIN Project Metadata - 2019 Churchill UAV Data",
695
      "name": "CANWIN Project Metadata - 2019 Churchill UAV Data",
            
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      "package_id": "b5f259b4-3ace-4750-bfb0-47c4e794082f",
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      "package_id": "b5f259b4-3ace-4750-bfb0-47c4e794082f",
            
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      "position": 16,
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      "position": 16,
            
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      "resCategory": "supplemental",
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      "resCategory": "supplemental",
            
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      "resource_type": null,
            
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      "size": 29221,
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      "size": 29221,
            
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      "state": "active",
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      "state": "active",
            
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      "url": 
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      "url": 
            
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/download/canwin_project_metadata_template2019churchill_harasyn.docx",
703
/download/canwin_project_metadata_template2019churchill_harasyn.docx",
            
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      "url_type": "upload"
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      "url_type": "upload"
            
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    }
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    }
            
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  ],
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  "rightsIdentifier": "CC-BY-NC-SA-4.0",
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  "rightsIdentifier": "CC-BY-NC-SA-4.0",
            
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  "rightsIdentifierScheme": "SPDX",
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  "rightsIdentifierScheme": "SPDX",
            
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  "rightsURI": "https://spdx.org/licenses/CC-BY-NC-SA-4.0.html",
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59],[-93.7822780979,58.9622307704],[-93.7839520373,58.5448288885]]]}",
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59],[-93.7822780979,58.9622307704],[-93.7839520373,58.5448288885]]]}",
            
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  "spatial_regions": "churchill",
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  "spatial_regions": "churchill",
            
723
  "startDate": "2019-07-28",
714
  "startDate": "2019-07-28",
            
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  "startDateType": "Collected",
715
  "startDateType": "Collected",
            
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  "state": "active",
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  "state": "active",
            
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  "status": "Complete",
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  "status": "Complete",
            
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  "subjectScheme": "",
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  "subjectScheme": "",
            
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  "tags": [
719
  "tags": [
            
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    {
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    {
            
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      "display_name": "Churchill estuary",
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      "display_name": "Churchill estuary",
            
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      "id": "f7d7cb9f-46ae-42af-8055-6ae5b8029c7a",
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      "id": "f7d7cb9f-46ae-42af-8055-6ae5b8029c7a",
            
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      "name": "Churchill estuary",
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      "name": "Churchill estuary",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "UAV",
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      "display_name": "UAV",
            
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      "id": "dd9d35dd-8475-43d3-aed7-43f75f64b8ce",
            
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      "name": "UAV",
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      "name": "UAV",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "aerial photos",
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      "display_name": "aerial photos",
            
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      "id": "14ba7276-8662-4338-ac0f-5d9ab3a0d8b0",
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      "id": "14ba7276-8662-4338-ac0f-5d9ab3a0d8b0",
            
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      "name": "aerial photos",
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      "name": "aerial photos",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
            
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    },
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    {
            
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      "display_name": "beluga",
            
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      "id": "286b2f82-a071-41cc-bc3b-7ea986233649",
            
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      "name": "beluga",
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      "name": "beluga",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
748
    {
            
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      "display_name": "boat",
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      "display_name": "boat",
            
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      "id": "b51f6a38-77f6-4e99-b83e-721cd7a05470",
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      "id": "b51f6a38-77f6-4e99-b83e-721cd7a05470",
            
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      "name": "boat",
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      "name": "boat",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "kayak",
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      "display_name": "kayak",
            
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      "id": "8383485f-fb93-42fd-a624-cb309b35ea78",
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      "id": "8383485f-fb93-42fd-a624-cb309b35ea78",
            
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      "name": "kayak",
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      "name": "kayak",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "video",
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      "display_name": "video",
            
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      "id": "2d1f3515-7c95-4d63-9ce8-829079ad26e9",
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      "id": "2d1f3515-7c95-4d63-9ce8-829079ad26e9",
            
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      "name": "video",
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      "name": "video",
            
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      "state": "active",
766
      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    }
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    }
            
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  ],
769
  ],
            
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  "theme": [
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  "theme": [
            
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    "8f8cd877-b037-4b1a-b928-f86d9e093741",
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    "8f8cd877-b037-4b1a-b928-f86d9e093741",
            
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    "3ec49cbb-4da6-4fe8-8d54-5b6ce03b49d9"
            
783
  ],
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  ],
            
784
  "title": "Churchill Beluga Boat Drone Imagery",
775
  "title": "Churchill Beluga Boat Drone Imagery",
            
785
  "titleType": "Alternative Title",
776
  "titleType": "Alternative Title",
            
786
  "type": "dataset",
777
  "type": "dataset",
            
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  "url": null,
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  "url": null,
            
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  "useTerms": "By accessing this data you agree to [CanWIN's Terms of 
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  "useTerms": "By accessing this data you agree to [CanWIN's Terms of 
            
789
anwin-data-statement/resource/5b942a87-ef4e-466e-8319-f588844e89c0).",
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anwin-data-statement/resource/5b942a87-ef4e-466e-8319-f588844e89c0).",
            
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  "variablesMeasured": "",
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  "variablesMeasured": "",
            
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}
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}