Változások
On Június 14, 2023, 11:18:04 (SAST),
-
Deleted resource sen_women_of_reproductive_age_15_49_csv.zip from Senegal: High Resolution Population Density Maps + Demographic Estimates
f | 1 | { | f | 1 | { |
2 | "author": "Data for Good at Meta", | 2 | "author": "Data for Good at Meta", | ||
3 | "author_email": "", | 3 | "author_email": "", | ||
4 | "creator_user_id": "34f7a594-935e-4ac6-b13c-8bb3b861b487", | 4 | "creator_user_id": "34f7a594-935e-4ac6-b13c-8bb3b861b487", | ||
5 | "extras": [], | 5 | "extras": [], | ||
6 | "groups": [ | 6 | "groups": [ | ||
7 | { | 7 | { | ||
8 | "description": "The Humanitarian Data Exchange (HDX) is an open | 8 | "description": "The Humanitarian Data Exchange (HDX) is an open | ||
9 | platform for sharing data across crises and organisations. Launched in | 9 | platform for sharing data across crises and organisations. Launched in | ||
10 | July 2014, the goal of HDX is to make humanitarian data easy to find | 10 | July 2014, the goal of HDX is to make humanitarian data easy to find | ||
11 | and use for analysis. Our growing collection of datasets has been | 11 | and use for analysis. Our growing collection of datasets has been | ||
12 | accessed by users in over 200 countries and territories.\r\n\r\nHDX is | 12 | accessed by users in over 200 countries and territories.\r\n\r\nHDX is | ||
13 | managed by OCHA's Centre for Humanitarian Data, which is located in | 13 | managed by OCHA's Centre for Humanitarian Data, which is located in | ||
14 | The Hague. OCHA is part of the United Nations Secretariat and is | 14 | The Hague. OCHA is part of the United Nations Secretariat and is | ||
15 | responsible for bringing together humanitarian actors to ensure a | 15 | responsible for bringing together humanitarian actors to ensure a | ||
16 | coherent response to emergencies. The HDX team includes OCHA staff and | 16 | coherent response to emergencies. The HDX team includes OCHA staff and | ||
17 | a number of consultants who are based in North America, Europe and | 17 | a number of consultants who are based in North America, Europe and | ||
18 | Africa.", | 18 | Africa.", | ||
19 | "display_name": "HDX: Humanitarian Data Exchange", | 19 | "display_name": "HDX: Humanitarian Data Exchange", | ||
20 | "id": "15791998-b8b5-41fa-841f-0393addadcbf", | 20 | "id": "15791998-b8b5-41fa-841f-0393addadcbf", | ||
21 | "image_display_url": | 21 | "image_display_url": | ||
22 | "https://data.humdata.org/images/homepage/logo-hdx.svg", | 22 | "https://data.humdata.org/images/homepage/logo-hdx.svg", | ||
23 | "name": "hdx-humanitarian-data-exchange", | 23 | "name": "hdx-humanitarian-data-exchange", | ||
24 | "title": "HDX: Humanitarian Data Exchange" | 24 | "title": "HDX: Humanitarian Data Exchange" | ||
25 | }, | 25 | }, | ||
26 | { | 26 | { | ||
27 | "description": "", | 27 | "description": "", | ||
28 | "display_name": "Population ", | 28 | "display_name": "Population ", | ||
29 | "id": "ad455715-07fc-421f-aef4-780b25b9c67a", | 29 | "id": "ad455715-07fc-421f-aef4-780b25b9c67a", | ||
30 | "image_display_url": "", | 30 | "image_display_url": "", | ||
31 | "name": "population", | 31 | "name": "population", | ||
32 | "title": "Population " | 32 | "title": "Population " | ||
33 | } | 33 | } | ||
34 | ], | 34 | ], | ||
35 | "id": "b2dbad02-ed55-4497-97b8-8377b91724fe", | 35 | "id": "b2dbad02-ed55-4497-97b8-8377b91724fe", | ||
36 | "isopen": true, | 36 | "isopen": true, | ||
37 | "license_id": "cc-by", | 37 | "license_id": "cc-by", | ||
38 | "license_title": "Creative Commons Attribution", | 38 | "license_title": "Creative Commons Attribution", | ||
39 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 39 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
40 | "maintainer": "Heiko Heilgendorff (OCL)", | 40 | "maintainer": "Heiko Heilgendorff (OCL)", | ||
41 | "maintainer_email": "[email protected]", | 41 | "maintainer_email": "[email protected]", | ||
42 | "metadata_created": "2021-06-04T11:21:16.687039", | 42 | "metadata_created": "2021-06-04T11:21:16.687039", | ||
n | 43 | "metadata_modified": "2023-06-14T09:17:50.282920", | n | 43 | "metadata_modified": "2023-06-14T09:18:04.222378", |
44 | "name": | 44 | "name": | ||
45 | enegal-high-resolution-population-density-maps-demographic-estimates", | 45 | enegal-high-resolution-population-density-maps-demographic-estimates", | ||
46 | "notes": "VERSION 1.5. The world's most accurate population | 46 | "notes": "VERSION 1.5. The world's most accurate population | ||
47 | datasets. Seven maps/datasets for the distribution of various | 47 | datasets. Seven maps/datasets for the distribution of various | ||
48 | populations in Senegal: (1) Overall population density (2) Women (3) | 48 | populations in Senegal: (1) Overall population density (2) Women (3) | ||
49 | Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages | 49 | Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages | ||
50 | 60+) (7) Women of reproductive age (ages 15-49).\r\n\r\n### | 50 | 60+) (7) Women of reproductive age (ages 15-49).\r\n\r\n### | ||
51 | Methodology\r\n\r\nThese high-resolution maps are created using | 51 | Methodology\r\n\r\nThese high-resolution maps are created using | ||
52 | machine learning techniques to identify buildings from commercially | 52 | machine learning techniques to identify buildings from commercially | ||
53 | available satellite images. This is then overlayed with general | 53 | available satellite images. This is then overlayed with general | ||
54 | population estimates based on publicly available census data and other | 54 | population estimates based on publicly available census data and other | ||
55 | population statistics at Columbia University. The resulting maps are | 55 | population statistics at Columbia University. The resulting maps are | ||
56 | the most detailed and actionable tools available for aid and research | 56 | the most detailed and actionable tools available for aid and research | ||
57 | organizations. For more information about the methodology used to | 57 | organizations. For more information about the methodology used to | ||
58 | create our high resolution population density maps and the demographic | 58 | create our high resolution population density maps and the demographic | ||
59 | distributions, click | 59 | distributions, click | ||
60 | -resolution-population-density-maps-demographic-estimates/)\r\n\r\nFor | 60 | -resolution-population-density-maps-demographic-estimates/)\r\n\r\nFor | ||
61 | information about how to use HDX to access these datasets, please | 61 | information about how to use HDX to access these datasets, please | ||
62 | visit: | 62 | visit: | ||
63 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | 63 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | ||
64 | to match the census population with the UN estimates are applied at | 64 | to match the census population with the UN estimates are applied at | ||
65 | the national level. The UN estimate for a given country (or | 65 | the national level. The UN estimate for a given country (or | ||
66 | state/territory) is divided by the total census estimate of population | 66 | state/territory) is divided by the total census estimate of population | ||
67 | for the given country. The resulting adjustment factor is multiplied | 67 | for the given country. The resulting adjustment factor is multiplied | ||
68 | by each administrative unit census value for the target year. This | 68 | by each administrative unit census value for the target year. This | ||
69 | preserves the relative population totals across administrative units | 69 | preserves the relative population totals across administrative units | ||
70 | while matching the UN total. More information can be found | 70 | while matching the UN total. More information can be found | ||
71 | ocs/census-information-for-high-resolution-population-density-maps/)", | 71 | ocs/census-information-for-high-resolution-population-density-maps/)", | ||
n | 72 | "num_resources": 5, | n | 72 | "num_resources": 4, |
73 | "num_tags": 7, | 73 | "num_tags": 7, | ||
74 | "organization": { | 74 | "organization": { | ||
75 | "approval_status": "approved", | 75 | "approval_status": "approved", | ||
76 | "created": "2022-07-04T08:06:45.420882", | 76 | "created": "2022-07-04T08:06:45.420882", | ||
77 | "description": "We work to build inclusion and participatory | 77 | "description": "We work to build inclusion and participatory | ||
78 | democracy in cities and urban spaces through empowering citizens, | 78 | democracy in cities and urban spaces through empowering citizens, | ||
79 | building trust and accountability in civic space, and capacitating | 79 | building trust and accountability in civic space, and capacitating | ||
80 | government. You can find our website | 80 | government. You can find our website | ||
81 | [here](https://opencitieslab.org/).", | 81 | [here](https://opencitieslab.org/).", | ||
82 | "id": "8e526815-d516-4f6c-9ae0-a4d62555c30c", | 82 | "id": "8e526815-d516-4f6c-9ae0-a4d62555c30c", | ||
83 | "image_url": | 83 | "image_url": | ||
84 | ttps://opencitieslab.org/odd/static/dist/img/ocl_logo_header-nav.png", | 84 | ttps://opencitieslab.org/odd/static/dist/img/ocl_logo_header-nav.png", | ||
85 | "is_organization": true, | 85 | "is_organization": true, | ||
86 | "name": "open-cities-lab", | 86 | "name": "open-cities-lab", | ||
87 | "revision_id": "35e0d462-e6b8-4c18-8743-e9361e136009", | 87 | "revision_id": "35e0d462-e6b8-4c18-8743-e9361e136009", | ||
88 | "state": "active", | 88 | "state": "active", | ||
89 | "title": "Open Cities Lab", | 89 | "title": "Open Cities Lab", | ||
90 | "type": "organization" | 90 | "type": "organization" | ||
91 | }, | 91 | }, | ||
92 | "owner_org": "8e526815-d516-4f6c-9ae0-a4d62555c30c", | 92 | "owner_org": "8e526815-d516-4f6c-9ae0-a4d62555c30c", | ||
93 | "private": false, | 93 | "private": false, | ||
94 | "relationships_as_object": [], | 94 | "relationships_as_object": [], | ||
95 | "relationships_as_subject": [], | 95 | "relationships_as_subject": [], | ||
96 | "resources": [ | 96 | "resources": [ | ||
97 | { | 97 | { | ||
98 | "cache_last_updated": null, | 98 | "cache_last_updated": null, | ||
99 | "cache_url": null, | 99 | "cache_url": null, | ||
n | 100 | "created": "2021-06-04T11:25:10.974019", | n | 100 | "created": "2021-06-04T11:25:30.067905", |
101 | "datastore_active": false, | ||||
102 | "description": "", | ||||
103 | "format": "geotiff", | ||||
104 | "hash": "", | ||||
105 | "id": "70afef22-8816-4106-83fc-297734aeca0f", | ||||
106 | "last_modified": null, | ||||
107 | "mimetype": null, | ||||
108 | "mimetype_inner": null, | ||||
109 | "name": "sen_women_of_reproductive_age_15_49_geotiff.zip", | ||||
110 | "package_id": "b2dbad02-ed55-4497-97b8-8377b91724fe", | ||||
111 | "position": 0, | ||||
112 | "resource_type": null, | ||||
113 | "revision_id": "806f2a2d-1da6-44ba-8314-f6d5c0ea9f72", | ||||
114 | "size": null, | ||||
115 | "state": "active", | ||||
116 | "url": | ||||
117 | 05fbf5680d6/download/sen_women_of_reproductive_age_15_49_geotiff.zip", | ||||
118 | "url_type": null | ||||
119 | }, | ||||
120 | { | ||||
121 | "cache_last_updated": null, | ||||
122 | "cache_url": null, | ||||
123 | "created": "2021-06-04T11:25:45.797372", | ||||
101 | "datastore_active": false, | 124 | "datastore_active": false, | ||
102 | "description": "", | 125 | "description": "", | ||
103 | "format": "CSV", | 126 | "format": "CSV", | ||
104 | "hash": "", | 127 | "hash": "", | ||
n | 105 | "id": "e7f925a8-e95b-4045-99a8-a604a54a0e96", | n | 128 | "id": "3f51d56a-1aa3-4708-a0ef-50aecbbacecb", |
106 | "last_modified": null, | 129 | "last_modified": null, | ||
n | 107 | "mimetype": null, | n | ||
108 | "mimetype_inner": null, | 130 | "mimetype": null, | ||
109 | "name": "sen_women_of_reproductive_age_15_49_csv.zip", | 131 | "mimetype_inner": null, | ||
132 | "name": "sen_youth_15_24_csv.zip", | ||||
110 | "package_id": "b2dbad02-ed55-4497-97b8-8377b91724fe", | 133 | "package_id": "b2dbad02-ed55-4497-97b8-8377b91724fe", | ||
n | 111 | "position": 0, | n | 134 | "position": 1, |
112 | "resource_type": null, | ||||
113 | "revision_id": "dc336447-5b81-447c-8bf3-fab606425101", | ||||
114 | "size": null, | ||||
115 | "state": "active", | ||||
116 | "url": | ||||
117 | 63-ae4eabbfcfe7/download/sen_women_of_reproductive_age_15_49_csv.zip", | ||||
118 | "url_type": null | 135 | "resource_type": null, | ||
136 | "revision_id": "806f2a2d-1da6-44ba-8314-f6d5c0ea9f72", | ||||
137 | "size": null, | ||||
138 | "state": "active", | ||||
139 | "url": | ||||
140 | d8c3253-b45c-4d56-9727-0b5ea559cf94/download/sen_youth_15_24_csv.zip", | ||||
141 | "url_type": null | ||||
119 | }, | 142 | }, | ||
120 | { | 143 | { | ||
n | 121 | "cache_last_updated": null, | n | ||
122 | "cache_url": null, | 144 | "cache_last_updated": null, | ||
145 | "cache_url": null, | ||||
123 | "created": "2021-06-04T11:25:30.067905", | 146 | "created": "2021-06-04T11:26:00.477386", | ||
124 | "datastore_active": false, | 147 | "datastore_active": false, | ||
125 | "description": "", | 148 | "description": "", | ||
126 | "format": "geotiff", | 149 | "format": "geotiff", | ||
127 | "hash": "", | 150 | "hash": "", | ||
n | 128 | "id": "70afef22-8816-4106-83fc-297734aeca0f", | n | 151 | "id": "61706a7f-8083-4825-ba9f-947320dbef38", |
129 | "last_modified": null, | 152 | "last_modified": null, | ||
n | 130 | "mimetype": null, | n | ||
131 | "mimetype_inner": null, | 153 | "mimetype": null, | ||
132 | "name": "sen_women_of_reproductive_age_15_49_geotiff.zip", | ||||
133 | "package_id": "b2dbad02-ed55-4497-97b8-8377b91724fe", | ||||
134 | "position": 1, | ||||
135 | "resource_type": null, | ||||
136 | "revision_id": "dc336447-5b81-447c-8bf3-fab606425101", | ||||
137 | "size": null, | ||||
138 | "state": "active", | ||||
139 | "url": | ||||
140 | 05fbf5680d6/download/sen_women_of_reproductive_age_15_49_geotiff.zip", | ||||
141 | "url_type": null | ||||
142 | }, | ||||
143 | { | ||||
144 | "cache_last_updated": null, | ||||
145 | "cache_url": null, | ||||
146 | "created": "2021-06-04T11:25:45.797372", | ||||
147 | "datastore_active": false, | ||||
148 | "description": "", | ||||
149 | "format": "CSV", | ||||
150 | "hash": "", | ||||
151 | "id": "3f51d56a-1aa3-4708-a0ef-50aecbbacecb", | ||||
152 | "last_modified": null, | ||||
153 | "mimetype": null, | 154 | "mimetype_inner": null, | ||
154 | "mimetype_inner": null, | ||||
155 | "name": "sen_youth_15_24_csv.zip", | 155 | "name": "sen_youth_15_24_geotiff.zip", | ||
156 | "package_id": "b2dbad02-ed55-4497-97b8-8377b91724fe", | 156 | "package_id": "b2dbad02-ed55-4497-97b8-8377b91724fe", | ||
157 | "position": 2, | 157 | "position": 2, | ||
158 | "resource_type": null, | 158 | "resource_type": null, | ||
n | 159 | "revision_id": "dc336447-5b81-447c-8bf3-fab606425101", | n | 159 | "revision_id": "806f2a2d-1da6-44ba-8314-f6d5c0ea9f72", |
160 | "size": null, | ||||
161 | "state": "active", | ||||
162 | "url": | ||||
163 | d8c3253-b45c-4d56-9727-0b5ea559cf94/download/sen_youth_15_24_csv.zip", | ||||
164 | "url_type": null | ||||
165 | }, | ||||
166 | { | ||||
167 | "cache_last_updated": null, | ||||
168 | "cache_url": null, | ||||
169 | "created": "2021-06-04T11:26:00.477386", | ||||
170 | "datastore_active": false, | ||||
171 | "description": "", | ||||
172 | "format": "geotiff", | ||||
173 | "hash": "", | ||||
174 | "id": "61706a7f-8083-4825-ba9f-947320dbef38", | ||||
175 | "last_modified": null, | ||||
176 | "mimetype": null, | ||||
177 | "mimetype_inner": null, | ||||
178 | "name": "sen_youth_15_24_geotiff.zip", | ||||
179 | "package_id": "b2dbad02-ed55-4497-97b8-8377b91724fe", | ||||
180 | "position": 3, | ||||
181 | "resource_type": null, | ||||
182 | "revision_id": "dc336447-5b81-447c-8bf3-fab606425101", | ||||
183 | "size": null, | 160 | "size": null, | ||
184 | "state": "active", | 161 | "state": "active", | ||
185 | "url": | 162 | "url": | ||
186 | 6f8-9912-435f-a65f-c7e2ad5289b8/download/sen_youth_15_24_geotiff.zip", | 163 | 6f8-9912-435f-a65f-c7e2ad5289b8/download/sen_youth_15_24_geotiff.zip", | ||
187 | "url_type": null | 164 | "url_type": null | ||
188 | }, | 165 | }, | ||
189 | { | 166 | { | ||
190 | "cache_last_updated": null, | 167 | "cache_last_updated": null, | ||
191 | "cache_url": null, | 168 | "cache_url": null, | ||
192 | "created": "2022-06-15T10:41:41.923019", | 169 | "created": "2022-06-15T10:41:41.923019", | ||
193 | "datastore_active": false, | 170 | "datastore_active": false, | ||
194 | "description": "The world's most accurate population datasets. | 171 | "description": "The world's most accurate population datasets. | ||
195 | Seven maps/datasets for the distribution of various populations in | 172 | Seven maps/datasets for the distribution of various populations in | ||
196 | Senegal: (1) Overall population density (2) Women (3) Men (4) Children | 173 | Senegal: (1) Overall population density (2) Women (3) Men (4) Children | ||
197 | (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of | 174 | (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of | ||
198 | reproductive age (ages 15-49).", | 175 | reproductive age (ages 15-49).", | ||
199 | "format": "", | 176 | "format": "", | ||
200 | "hash": "", | 177 | "hash": "", | ||
201 | "id": "f84968a5-1fe0-4885-9864-11202b9fadd1", | 178 | "id": "f84968a5-1fe0-4885-9864-11202b9fadd1", | ||
202 | "last_modified": null, | 179 | "last_modified": null, | ||
203 | "mimetype": null, | 180 | "mimetype": null, | ||
204 | "mimetype_inner": null, | 181 | "mimetype_inner": null, | ||
205 | "name": "Senegal high resolution population density maps ", | 182 | "name": "Senegal high resolution population density maps ", | ||
206 | "package_id": "b2dbad02-ed55-4497-97b8-8377b91724fe", | 183 | "package_id": "b2dbad02-ed55-4497-97b8-8377b91724fe", | ||
n | 207 | "position": 4, | n | 184 | "position": 3, |
208 | "resource_type": null, | 185 | "resource_type": null, | ||
t | 209 | "revision_id": "dc336447-5b81-447c-8bf3-fab606425101", | t | 186 | "revision_id": "806f2a2d-1da6-44ba-8314-f6d5c0ea9f72", |
210 | "size": null, | 187 | "size": null, | ||
211 | "state": "active", | 188 | "state": "active", | ||
212 | "url": | 189 | "url": | ||
213 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-sen", | 190 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-sen", | ||
214 | "url_type": null | 191 | "url_type": null | ||
215 | } | 192 | } | ||
216 | ], | 193 | ], | ||
217 | "revision_id": "8bba3e0b-5341-47f2-83b7-5a8c7207e00e", | 194 | "revision_id": "8bba3e0b-5341-47f2-83b7-5a8c7207e00e", | ||
218 | "state": "active", | 195 | "state": "active", | ||
219 | "tags": [ | 196 | "tags": [ | ||
220 | { | 197 | { | ||
221 | "display_name": "children", | 198 | "display_name": "children", | ||
222 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | 199 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | ||
223 | "name": "children", | 200 | "name": "children", | ||
224 | "state": "active", | 201 | "state": "active", | ||
225 | "vocabulary_id": null | 202 | "vocabulary_id": null | ||
226 | }, | 203 | }, | ||
227 | { | 204 | { | ||
228 | "display_name": "elderly", | 205 | "display_name": "elderly", | ||
229 | "id": "9c11b077-a76b-4a95-b6ee-afb6c112f48c", | 206 | "id": "9c11b077-a76b-4a95-b6ee-afb6c112f48c", | ||
230 | "name": "elderly", | 207 | "name": "elderly", | ||
231 | "state": "active", | 208 | "state": "active", | ||
232 | "vocabulary_id": null | 209 | "vocabulary_id": null | ||
233 | }, | 210 | }, | ||
234 | { | 211 | { | ||
235 | "display_name": "population density", | 212 | "display_name": "population density", | ||
236 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | 213 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | ||
237 | "name": "population density", | 214 | "name": "population density", | ||
238 | "state": "active", | 215 | "state": "active", | ||
239 | "vocabulary_id": null | 216 | "vocabulary_id": null | ||
240 | }, | 217 | }, | ||
241 | { | 218 | { | ||
242 | "display_name": "senegal", | 219 | "display_name": "senegal", | ||
243 | "id": "a044a0a6-098c-4aa9-a828-14462af6be1b", | 220 | "id": "a044a0a6-098c-4aa9-a828-14462af6be1b", | ||
244 | "name": "senegal", | 221 | "name": "senegal", | ||
245 | "state": "active", | 222 | "state": "active", | ||
246 | "vocabulary_id": null | 223 | "vocabulary_id": null | ||
247 | }, | 224 | }, | ||
248 | { | 225 | { | ||
249 | "display_name": "women", | 226 | "display_name": "women", | ||
250 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | 227 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | ||
251 | "name": "women", | 228 | "name": "women", | ||
252 | "state": "active", | 229 | "state": "active", | ||
253 | "vocabulary_id": null | 230 | "vocabulary_id": null | ||
254 | }, | 231 | }, | ||
255 | { | 232 | { | ||
256 | "display_name": "women of reproductive age", | 233 | "display_name": "women of reproductive age", | ||
257 | "id": "a1f9dfb8-316b-40bd-8182-5e3afdf9237c", | 234 | "id": "a1f9dfb8-316b-40bd-8182-5e3afdf9237c", | ||
258 | "name": "women of reproductive age", | 235 | "name": "women of reproductive age", | ||
259 | "state": "active", | 236 | "state": "active", | ||
260 | "vocabulary_id": null | 237 | "vocabulary_id": null | ||
261 | }, | 238 | }, | ||
262 | { | 239 | { | ||
263 | "display_name": "youth", | 240 | "display_name": "youth", | ||
264 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | 241 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | ||
265 | "name": "youth", | 242 | "name": "youth", | ||
266 | "state": "active", | 243 | "state": "active", | ||
267 | "vocabulary_id": null | 244 | "vocabulary_id": null | ||
268 | } | 245 | } | ||
269 | ], | 246 | ], | ||
270 | "title": "Senegal: High Resolution Population Density Maps + | 247 | "title": "Senegal: High Resolution Population Density Maps + | ||
271 | Demographic Estimates", | 248 | Demographic Estimates", | ||
272 | "type": "dataset", | 249 | "type": "dataset", | ||
273 | "url": | 250 | "url": | ||
274 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-sen", | 251 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-sen", | ||
275 | "version": "" | 252 | "version": "" | ||
276 | } | 253 | } |