Changes
On April 7, 2022 at 9:59:04 AM CDT, Casey Clair:
-
Changed value of field
methodDescrioption
toMaterials and methods
in Churchill Beluga Boat Drone Imagery -
Changed value of field
methodUrl
tohttps://doi.org/10.1139/juvs-2021-0024
in Churchill Beluga Boat Drone Imagery -
Changed value of field
related_instruments
to[]
in Churchill Beluga Boat Drone Imagery
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2 | "Creator": "Creator", | 2 | "Creator": "Creator", | ||
3 | "Date": "2019-08-09", | 3 | "Date": "2019-08-09", | ||
4 | "IdentifierType": "DOI", | 4 | "IdentifierType": "DOI", | ||
5 | "PublicationYear": "2022", | 5 | "PublicationYear": "2022", | ||
6 | "Publisher": "CanWIN", | 6 | "Publisher": "CanWIN", | ||
7 | "RelatedIdentifierType": "URL", | 7 | "RelatedIdentifierType": "URL", | ||
8 | "RelationType": "IsSupplementTo", | 8 | "RelationType": "IsSupplementTo", | ||
9 | "ResourceType": "imagery", | 9 | "ResourceType": "imagery", | ||
10 | "Rights": "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 | 10 | "Rights": "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 | ||
11 | International", | 11 | International", | ||
12 | "Version": "1.0", | 12 | "Version": "1.0", | ||
13 | "accessTerms": "CanWIN datasets are licensed individually, however | 13 | "accessTerms": "CanWIN datasets are licensed individually, however | ||
14 | most are licensed under the Creative Commons Attribution 4.0 | 14 | most are licensed under the Creative Commons Attribution 4.0 | ||
15 | International (CC BY 4.0) Public License. Details for the licence | 15 | International (CC BY 4.0) Public License. Details for the licence | ||
16 | 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 | ||
17 | dataset. \r\nBy using data and information provided on this site you | 17 | dataset. \r\nBy using data and information provided on this site you | ||
18 | accept the terms and conditions of the License. Unless otherwise | 18 | accept the terms and conditions of the License. Unless otherwise | ||
19 | specified, the license grants the rights to the public to use and | 19 | specified, the license grants the rights to the public to use and | ||
20 | share the data and results derived therefrom as long as the proper | 20 | share the data and results derived therefrom as long as the proper | ||
21 | acknowledgment is given to the data licensor (citation), that any | 21 | acknowledgment is given to the data licensor (citation), that any | ||
22 | alteration to the data is clearly indicated, and that a link to the | 22 | alteration to the data is clearly indicated, and that a link to the | ||
23 | original data and the license is made available.", | 23 | original data and the license is made available.", | ||
24 | "activityCollectionType": "Field Measurement", | 24 | "activityCollectionType": "Field Measurement", | ||
25 | "analyticalMethodName": "", | 25 | "analyticalMethodName": "", | ||
26 | "author": null, | 26 | "author": null, | ||
27 | "author_email": null, | 27 | "author_email": null, | ||
28 | "campaignEndDate": "2019-08-09", | 28 | "campaignEndDate": "2019-08-09", | ||
29 | "campaignStartDate": "2019-07-28", | 29 | "campaignStartDate": "2019-07-28", | ||
30 | "comments": "", | 30 | "comments": "", | ||
31 | "contributorName": "Chan, Wayne", | 31 | "contributorName": "Chan, Wayne", | ||
32 | "contributorType": "DataCurator", | 32 | "contributorType": "DataCurator", | ||
33 | "creatorName": [ | 33 | "creatorName": [ | ||
34 | { | 34 | { | ||
35 | "author": "Harasyn, Madison", | 35 | "author": "Harasyn, Madison", | ||
36 | "creatorAffiliation": "Centre for Earth Observation Science - | 36 | "creatorAffiliation": "Centre for Earth Observation Science - | ||
37 | University of Manitoba", | 37 | University of Manitoba", | ||
38 | "creatorEmail": "Madison.harasyn@umanitoba.ca", | 38 | "creatorEmail": "Madison.harasyn@umanitoba.ca", | ||
39 | "creatorNameIdentifier": | 39 | "creatorNameIdentifier": | ||
40 | "https://orcid.org/0000-0002-5741-6766", | 40 | "https://orcid.org/0000-0002-5741-6766", | ||
41 | "nameIdentifierScheme": "ORCID", | 41 | "nameIdentifierScheme": "ORCID", | ||
42 | "nameType": "Personal", | 42 | "nameType": "Personal", | ||
43 | "schemeURI": "http://orcid.org/" | 43 | "schemeURI": "http://orcid.org/" | ||
44 | }, | 44 | }, | ||
45 | { | 45 | { | ||
46 | "author": "Barber, David", | 46 | "author": "Barber, David", | ||
47 | "creatorAffiliation": "Centre for Earth Observation Science - | 47 | "creatorAffiliation": "Centre for Earth Observation Science - | ||
48 | University of Manitoba", | 48 | University of Manitoba", | ||
49 | "creatorEmail": "david.barber@umanitoba.ca", | 49 | "creatorEmail": "david.barber@umanitoba.ca", | ||
50 | "creatorNameIdentifier": "0000-0001-9466-3291", | 50 | "creatorNameIdentifier": "0000-0001-9466-3291", | ||
51 | "nameIdentifierScheme": "ORCID", | 51 | "nameIdentifierScheme": "ORCID", | ||
52 | "nameType": "Personal", | 52 | "nameType": "Personal", | ||
53 | "schemeURI": "http://orcid.org/" | 53 | "schemeURI": "http://orcid.org/" | ||
54 | } | 54 | } | ||
55 | ], | 55 | ], | ||
56 | "creator_user_id": "cde7b848-a882-4fc7-97c9-670417bd6b43", | 56 | "creator_user_id": "cde7b848-a882-4fc7-97c9-670417bd6b43", | ||
57 | "dataCuratorAffiliation": "Centre for Earth Observation Science - | 57 | "dataCuratorAffiliation": "Centre for Earth Observation Science - | ||
58 | University of Manitoba", | 58 | University of Manitoba", | ||
59 | "dataCuratorEmail": "wayne.chan@umanitoba.ca", | 59 | "dataCuratorEmail": "wayne.chan@umanitoba.ca", | ||
60 | "datasetCitation": "", | 60 | "datasetCitation": "", | ||
61 | "datasetLevel": "1.1", | 61 | "datasetLevel": "1.1", | ||
62 | "datasetPublisher": "CanWIN", | 62 | "datasetPublisher": "CanWIN", | ||
63 | "dateType": "Updated", | 63 | "dateType": "Updated", | ||
64 | "descriptionType": "Abstract", | 64 | "descriptionType": "Abstract", | ||
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66 | "embargoDate": "", | 66 | "embargoDate": "", | ||
67 | "endDate": "2019-08-09", | 67 | "endDate": "2019-08-09", | ||
68 | "endDateType": "Other", | 68 | "endDateType": "Other", | ||
69 | "frequency": "Not planned", | 69 | "frequency": "Not planned", | ||
70 | "funderIdentifierType": "", | 70 | "funderIdentifierType": "", | ||
71 | "funderName": "", | 71 | "funderName": "", | ||
72 | "funderSchemeURI": "", | 72 | "funderSchemeURI": "", | ||
73 | "groups": [ | 73 | "groups": [ | ||
74 | { | 74 | { | ||
n | 75 | "description": "Inland water features, drainage systems and | n | 75 | "description": "Features and characteristics of salt water |
76 | their characteristics. Examples of data you can find here include | 76 | bodies.\r\n\r\nIn CEOS, related research themes include | ||
77 | river and lake data, water quality data. \r\n\r\nIn CEOS, related | 77 | biogeochemistry, modelling, marine mammals, oil spill response, | ||
78 | research themes include biogeochemistry, Inland lakes and waters, | ||||
79 | modelling, remote sensing and technology, trace metals and | 78 | physical oceanography, remote sensing and technology and trace metals | ||
80 | contaminants.", | 79 | and contaminants", | ||
81 | "display_name": "Freshwater", | 80 | "display_name": "Marine", | ||
82 | "id": "8f8cd877-b037-4b1a-b928-f86d9e093741", | 81 | "id": "98238b1c-5be8-41ad-8c6e-74cdc4f5f369", | ||
83 | "image_display_url": | 82 | "image_display_url": | ||
n | 84 | /data/uploads/group/2021-10-31-211937.658599hyinspirehydrography.svg", | n | 83 | ata/uploads/group/2021-10-31-211516.365746ofinspireoceanographic.svg", |
85 | "name": "freshwater", | 84 | "name": "marine", | ||
86 | "title": "Freshwater" | 85 | "title": "Marine" | ||
87 | } | 86 | } | ||
88 | ], | 87 | ], | ||
89 | "id": "b5f259b4-3ace-4750-bfb0-47c4e794082f", | 88 | "id": "b5f259b4-3ace-4750-bfb0-47c4e794082f", | ||
90 | "isopen": false, | 89 | "isopen": false, | ||
91 | "keywords": "AERIAL PHOTOGRAPHS,Beluga,Churchill estuary,Unmanned | 90 | "keywords": "AERIAL PHOTOGRAPHS,Beluga,Churchill estuary,Unmanned | ||
92 | Aerial Vehicle,boat,kayak,video", | 91 | Aerial Vehicle,boat,kayak,video", | ||
93 | "kvSchemeURI": | 92 | "kvSchemeURI": | ||
94 | "https://www.polardata.ca/pdcinput/public/keywordlibrary ; | 93 | "https://www.polardata.ca/pdcinput/public/keywordlibrary ; | ||
95 | ps://gcmd.earthdata.nasa.gov/KeywordViewer/scheme/all?gtm_scheme=all", | 94 | ps://gcmd.earthdata.nasa.gov/KeywordViewer/scheme/all?gtm_scheme=all", | ||
96 | "laboratory": "CEOS", | 95 | "laboratory": "CEOS", | ||
97 | "licenceShemeURI": "https://spdx.org/licenses", | 96 | "licenceShemeURI": "https://spdx.org/licenses", | ||
98 | "licenceType": "Open", | 97 | "licenceType": "Open", | ||
99 | "license_id": null, | 98 | "license_id": null, | ||
100 | "license_title": null, | 99 | "license_title": null, | ||
101 | "maintainer": null, | 100 | "maintainer": null, | ||
102 | "maintainer_email": null, | 101 | "maintainer_email": null, | ||
103 | "metadata_created": "2022-02-04T19:17:36.940301", | 102 | "metadata_created": "2022-02-04T19:17:36.940301", | ||
n | 104 | "metadata_modified": "2022-03-24T15:31:54.248000", | n | 103 | "metadata_modified": "2022-04-07T14:59:04.302332", |
105 | "methodCitation": "", | 104 | "methodCitation": "", | ||
n | 106 | "methodDescrioption": "", | n | 105 | "methodDescrioption": "Materials and methods", |
107 | "methodDescriptionType": "Methods", | 106 | "methodDescriptionType": "Methods", | ||
108 | "methodLink": "", | 107 | "methodLink": "", | ||
109 | "methodSummary": "", | 108 | "methodSummary": "", | ||
n | 110 | "methodUrl": "", | n | 109 | "methodUrl": "https://doi.org/10.1139/juvs-2021-0024", |
111 | "name": "churchill-beluga-boat-drone-imagery", | 110 | "name": "churchill-beluga-boat-drone-imagery", | ||
112 | "northBoundLatitude": "58.8195795207", | 111 | "northBoundLatitude": "58.8195795207", | ||
113 | "notes": "Aerial imagery surveys are commonly used in marine mammal | 112 | "notes": "Aerial imagery surveys are commonly used in marine mammal | ||
114 | research to determine population size, habitat distribution and | 113 | research to determine population size, habitat distribution and | ||
115 | habitat use. Analysis of aerial photos involves hours of manually | 114 | habitat use. Analysis of aerial photos involves hours of manually | ||
116 | identifying individuals present in each image and converting raw | 115 | identifying individuals present in each image and converting raw | ||
117 | counts into useable biological statistics. Our research proposes the | 116 | counts into useable biological statistics. Our research proposes the | ||
118 | use of deep learning algorithms as an assistive technology to increase | 117 | use of deep learning algorithms as an assistive technology to increase | ||
119 | the efficiency of the marine mammal research workflow. To test the | 118 | the efficiency of the marine mammal research workflow. To test the | ||
120 | feasibility of this proposal, the existing YOLOv4 convolutional neural | 119 | feasibility of this proposal, the existing YOLOv4 convolutional neural | ||
121 | network model was trained to detect belugas, kayaks and motorized | 120 | network model was trained to detect belugas, kayaks and motorized | ||
122 | boats in unmanned aerial vehicle (UAV) imagery. Computer-based object | 121 | boats in unmanned aerial vehicle (UAV) imagery. Computer-based object | ||
123 | detection achieved an average precision of 61.17% for belugas, 98.58% | 122 | detection achieved an average precision of 61.17% for belugas, 98.58% | ||
124 | for boats, and 95.97% for kayaks. We then tested the performance of | 123 | for boats, and 95.97% for kayaks. We then tested the performance of | ||
125 | computer vision tracking of belugas and manned watercraft in UAV | 124 | computer vision tracking of belugas and manned watercraft in UAV | ||
126 | videos using the DeepSORT tracking algorithm, achieving a multiple | 125 | videos using the DeepSORT tracking algorithm, achieving a multiple | ||
127 | object tracking accuracy (MOTA) ranging from 37% \u2013 88% and | 126 | object tracking accuracy (MOTA) ranging from 37% \u2013 88% and | ||
128 | multiple object tracking precision (MOTP) between 63% \u2013 86%. | 127 | multiple object tracking precision (MOTP) between 63% \u2013 86%. | ||
129 | Results from this research indicate that deep learning technology can | 128 | Results from this research indicate that deep learning technology can | ||
130 | perform at a similar caliber as human annotators in beluga and | 129 | perform at a similar caliber as human annotators in beluga and | ||
131 | watercraft detection and tracking, allowing for larger datasets to be | 130 | watercraft detection and tracking, allowing for larger datasets to be | ||
132 | processed within a fraction of the time. ", | 131 | processed within a fraction of the time. ", | ||
133 | "num_resources": 16, | 132 | "num_resources": 16, | ||
134 | "num_tags": 7, | 133 | "num_tags": 7, | ||
135 | "organization": { | 134 | "organization": { | ||
136 | "approval_status": "approved", | 135 | "approval_status": "approved", | ||
137 | "created": "2017-07-21T13:15:49.935872", | 136 | "created": "2017-07-21T13:15:49.935872", | ||
138 | "description": "The Centre for Earth Observation Science (CEOS) | 137 | "description": "The Centre for Earth Observation Science (CEOS) | ||
139 | was established in 1994 with a mandate to research, preserve and | 138 | was established in 1994 with a mandate to research, preserve and | ||
140 | communicate knowledge of Earth system processes using the technologies | 139 | communicate knowledge of Earth system processes using the technologies | ||
141 | of Earth Observation Science. Research is multidisciplinary and | 140 | of Earth Observation Science. Research is multidisciplinary and | ||
142 | collaborative seeking to understand the complex interrelationships | 141 | collaborative seeking to understand the complex interrelationships | ||
143 | between elements of Earth systems, and how these systems will likely | 142 | between elements of Earth systems, and how these systems will likely | ||
144 | respond to climate change. Although researchers have worked in many | 143 | respond to climate change. Although researchers have worked in many | ||
145 | regions, the Arctic marine system has always been a unifying focus of | 144 | regions, the Arctic marine system has always been a unifying focus of | ||
146 | activity.\r\n\r\nIn 2012, CEOS, along with the Greenland Climate | 145 | activity.\r\n\r\nIn 2012, CEOS, along with the Greenland Climate | ||
147 | Research Centre (GCRC, Nuuk, Greenland) and the Arctic Research Centre | 146 | Research Centre (GCRC, Nuuk, Greenland) and the Arctic Research Centre | ||
148 | (ARC, Aarhus, Denmark) established the Arctic Science Partnership, | 147 | (ARC, Aarhus, Denmark) established the Arctic Science Partnership, | ||
149 | thereby integrating academic and research initiatives.\r\n\r\nAreas of | 148 | thereby integrating academic and research initiatives.\r\n\r\nAreas of | ||
150 | existing research activity are divided among key themes:\r\n\r\nArctic | 149 | existing research activity are divided among key themes:\r\n\r\nArctic | ||
151 | Anthropology/Paleoclimatology: LiDAR scanning and digital site | 150 | Anthropology/Paleoclimatology: LiDAR scanning and digital site | ||
152 | preservation, archaeo-geophysics, permafrost degredation, lithic | 151 | preservation, archaeo-geophysics, permafrost degredation, lithic | ||
153 | morphometrics, zooarchaeology, proxy studies, paleodistribution of sea | 152 | morphometrics, zooarchaeology, proxy studies, paleodistribution of sea | ||
154 | ice, landscape learning, Paleo-Eskimo culture, Thule Inuit culture, | 153 | ice, landscape learning, Paleo-Eskimo culture, Thule Inuit culture, | ||
155 | ethnographic analogy, traditional knowledge, climate change and | 154 | ethnographic analogy, traditional knowledge, climate change and | ||
156 | northern heritage resource management.\r\n\r\nAtmospheric | 155 | northern heritage resource management.\r\n\r\nAtmospheric | ||
157 | Studies/Meteorology: Boundary layer, precipitation, clouds, storms and | 156 | Studies/Meteorology: Boundary layer, precipitation, clouds, storms and | ||
158 | extreme weather, circulation, eddy correlations, polar vortex, | 157 | extreme weather, circulation, eddy correlations, polar vortex, | ||
159 | climate, teleconnections, geophysical fluid dynamics, flux and energy | 158 | climate, teleconnections, geophysical fluid dynamics, flux and energy | ||
160 | budgets, ocean-sea ice-atmosphere interface, radiative transfer, ice | 159 | budgets, ocean-sea ice-atmosphere interface, radiative transfer, ice | ||
161 | albedo feedback, cloud radiative forcing, pCO2. | 160 | albedo feedback, cloud radiative forcing, pCO2. | ||
162 | \r\n\r\nBiogeochemistry: Organic carbon, greenhouse gases, bubbles, | 161 | \r\n\r\nBiogeochemistry: Organic carbon, greenhouse gases, bubbles, | ||
163 | Ikaite, carbonate chemistry, CO2 fluxes, mercury and other trace | 162 | Ikaite, carbonate chemistry, CO2 fluxes, mercury and other trace | ||
164 | metals, minerals, hydrocarbons, brine processes, otolith | 163 | metals, minerals, hydrocarbons, brine processes, otolith | ||
165 | microchemistry, sediments, biomarkers. \r\n\r\nContaminants: Mercury, | 164 | microchemistry, sediments, biomarkers. \r\n\r\nContaminants: Mercury, | ||
166 | trace metals, PAHs, source, transport, transformation, pathways, | 165 | trace metals, PAHs, source, transport, transformation, pathways, | ||
167 | bioaccumulations, marine ecosystems, marine chemistry. \r\nEarth | 166 | bioaccumulations, marine ecosystems, marine chemistry. \r\nEarth | ||
168 | Observation Science: Active and passive microwave, LiDAR, EM | 167 | Observation Science: Active and passive microwave, LiDAR, EM | ||
169 | induction, spatial-temporal analysis, forward and inverse scattering | 168 | induction, spatial-temporal analysis, forward and inverse scattering | ||
170 | models, complex permittivity, ocean colour, ocean surface roughness, | 169 | models, complex permittivity, ocean colour, ocean surface roughness, | ||
171 | NIR, TIR, satellite telemetry, GPS. Ice-Associated Biology: | 170 | NIR, TIR, satellite telemetry, GPS. Ice-Associated Biology: | ||
172 | Biophysical processes, primary production; ice algae, ice | 171 | Biophysical processes, primary production; ice algae, ice | ||
173 | microbiology, bio-optics, under-ice phytoplankton. \r\n\r\nInland | 172 | microbiology, bio-optics, under-ice phytoplankton. \r\n\r\nInland | ||
174 | Lakes and Waters: Hydrologic connectivity, watershed systems, sediment | 173 | Lakes and Waters: Hydrologic connectivity, watershed systems, sediment | ||
175 | transport, nutrient transport, contaminants, landscape processes, | 174 | transport, nutrient transport, contaminants, landscape processes, | ||
176 | remote sensing, freshwater-marine coupling. Marine Mammals: Seals, | 175 | remote sensing, freshwater-marine coupling. Marine Mammals: Seals, | ||
177 | whales, habitat, conservation, satellite telemetry, distribution, | 176 | whales, habitat, conservation, satellite telemetry, distribution, | ||
178 | population studies, prey behaviour, bioacoustics.\r\n\r\nModelling: | 177 | population studies, prey behaviour, bioacoustics.\r\n\r\nModelling: | ||
179 | Simulation of sea ice and oceanic regional processes, Nucleus for | 178 | Simulation of sea ice and oceanic regional processes, Nucleus for | ||
180 | European Modelling of the Ocean (NEMO), ice-ocean modelling and | 179 | European Modelling of the Ocean (NEMO), ice-ocean modelling and | ||
181 | interactions, hind cast simulations and projections for sea ice state | 180 | interactions, hind cast simulations and projections for sea ice state | ||
182 | and ocean variables based on CMIP5 scenarios and MIROC5 forcing, | 181 | and ocean variables based on CMIP5 scenarios and MIROC5 forcing, | ||
183 | validation.\r\n\r\nOceanography: Circulation, temperature, in-flow and | 182 | validation.\r\n\r\nOceanography: Circulation, temperature, in-flow and | ||
184 | out-flow shelves, water dynamics, microturbulence, Beaufort Gyre, eddy | 183 | out-flow shelves, water dynamics, microturbulence, Beaufort Gyre, eddy | ||
185 | correlations.\r\n\r\nSea Ice Geophysics:Thermodynamic and dynamic | 184 | correlations.\r\n\r\nSea Ice Geophysics:Thermodynamic and dynamic | ||
186 | processes, extreme ice features and hazards, snow, ridges, | 185 | processes, extreme ice features and hazards, snow, ridges, | ||
187 | polynyas.\r\n\r\nTraditional and Local Knowledge: Indigenous cultures, | 186 | polynyas.\r\n\r\nTraditional and Local Knowledge: Indigenous cultures, | ||
188 | Inuit, Inuvialuit, oral history, toponomy, mobility and settlement, | 187 | Inuit, Inuvialuit, oral history, toponomy, mobility and settlement, | ||
189 | hunting, food security, sea ice use, community-based research, | 188 | hunting, food security, sea ice use, community-based research, | ||
190 | community-based monitoring, two ways of knowing.", | 189 | community-based monitoring, two ways of knowing.", | ||
191 | "id": "9e21f6b6-d13f-4ba2-a379-fd962f507071", | 190 | "id": "9e21f6b6-d13f-4ba2-a379-fd962f507071", | ||
192 | "image_url": "2021-11-13-003953.952874UMLogoHORZ.jpg", | 191 | "image_url": "2021-11-13-003953.952874UMLogoHORZ.jpg", | ||
193 | "is_organization": true, | 192 | "is_organization": true, | ||
194 | "name": "ceos2", | 193 | "name": "ceos2", | ||
195 | "state": "active", | 194 | "state": "active", | ||
196 | "title": "CEOS", | 195 | "title": "CEOS", | ||
197 | "type": "organization" | 196 | "type": "organization" | ||
198 | }, | 197 | }, | ||
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200 | "private": false, | 199 | "private": false, | ||
201 | "relatedIdentifier": "", | 200 | "relatedIdentifier": "", | ||
202 | "related_campaigns": "[]", | 201 | "related_campaigns": "[]", | ||
203 | "related_deployments": "[\"2f3631e0-419d-4565-81b0-24ad63465939\"]", | 202 | "related_deployments": "[\"2f3631e0-419d-4565-81b0-24ad63465939\"]", | ||
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205 | "related_platforms": "[\"75e924c1-f565-4de2-8a1b-51321273bad7\"]", | 204 | "related_platforms": "[\"75e924c1-f565-4de2-8a1b-51321273bad7\"]", | ||
206 | "related_programs": "[]", | 205 | "related_programs": "[]", | ||
207 | "related_publications": | 206 | "related_publications": | ||
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209 | "relationships_as_object": [], | 208 | "relationships_as_object": [], | ||
210 | "relationships_as_subject": [], | 209 | "relationships_as_subject": [], | ||
211 | "resourceTypeGeneral": "Dataset", | 210 | "resourceTypeGeneral": "Dataset", | ||
212 | "resources": [ | 211 | "resources": [ | ||
213 | { | 212 | { | ||
214 | "cache_last_updated": null, | 213 | "cache_last_updated": null, | ||
215 | "cache_url": null, | 214 | "cache_url": null, | ||
216 | "created": "2022-02-09T19:01:26.701129", | 215 | "created": "2022-02-09T19:01:26.701129", | ||
217 | "datastore_active": false, | 216 | "datastore_active": false, | ||
218 | "datastore_contains_all_records_of_source_file": false, | 217 | "datastore_contains_all_records_of_source_file": false, | ||
219 | "description": "Taken on June 13, 2018 in the Churchill Estuary | 218 | "description": "Taken on June 13, 2018 in the Churchill Estuary | ||
220 | as part of the Beluga Boat Study.", | 219 | as part of the Beluga Boat Study.", | ||
221 | "format": "JPEG", | 220 | "format": "JPEG", | ||
222 | "hash": "", | 221 | "hash": "", | ||
223 | "id": "e028a59d-284b-4502-acad-4aaf0e1776e1", | 222 | "id": "e028a59d-284b-4502-acad-4aaf0e1776e1", | ||
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225 | "metadata_modified": "2022-02-09T19:20:44.954729", | 224 | "metadata_modified": "2022-02-09T19:20:44.954729", | ||
226 | "mimetype": "image/jpeg", | 225 | "mimetype": "image/jpeg", | ||
227 | "mimetype_inner": null, | 226 | "mimetype_inner": null, | ||
228 | "name": "Churchill Estuary - Madison Harasyn, David Barber", | 227 | "name": "Churchill Estuary - Madison Harasyn, David Barber", | ||
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237 | "url_type": "upload" | 236 | "url_type": "upload" | ||
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609 | "description": "CANWIN metadata templates are filled out for | 608 | "description": "CANWIN metadata templates are filled out for | ||
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633 | "rightsIdentifierScheme": "SPDX", | 632 | "rightsIdentifierScheme": "SPDX", | ||
634 | "rightsURI": "https://spdx.org/licenses/CC-BY-NC-SA-4.0.html", | 633 | "rightsURI": "https://spdx.org/licenses/CC-BY-NC-SA-4.0.html", | ||
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640 | "startDateType": "Collected", | 639 | "startDateType": "Collected", | ||
641 | "state": "active", | 640 | "state": "active", | ||
642 | "status": "Complete", | 641 | "status": "Complete", | ||
643 | "subjectScheme": "Polar Data Catalogue,Global Change Master | 642 | "subjectScheme": "Polar Data Catalogue,Global Change Master | ||
644 | Directory", | 643 | Directory", | ||
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680 | }, | 679 | }, | ||
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702 | "titleType": "Alternative Title", | 701 | "titleType": "Alternative Title", | ||
703 | "type": "dataset", | 702 | "type": "dataset", | ||
704 | "url": null, | 703 | "url": null, | ||
705 | "useTerms": "By accessing this data you agree to [CanWIN's Terms of | 704 | "useTerms": "By accessing this data you agree to [CanWIN's Terms of | ||
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