Zmiany
On June 14, 2023, 11:38:27 (SAST),
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Deleted resource nga_women_2020_csv.zip from Nigeria: 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 | ], | ||
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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": "2021-06-03T14:01:21.364366", | 42 | "metadata_created": "2021-06-03T14:01:21.364366", | ||
n | 43 | "metadata_modified": "2023-06-14T09:37:15.320642", | n | 43 | "metadata_modified": "2023-06-14T09:38:27.068807", |
44 | "name": | 44 | "name": | ||
45 | igeria-high-resolution-population-density-maps-demographic-estimates", | 45 | igeria-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 Nigeria: (1) Overall population density (2) Women (3) | 48 | populations in Nigeria: (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": 8, | n | 72 | "num_resources": 7, |
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/).", | ||
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88 | "state": "active", | 88 | "state": "active", | ||
89 | "title": "Open Cities Lab", | 89 | "title": "Open Cities Lab", | ||
90 | "type": "organization" | 90 | "type": "organization" | ||
91 | }, | 91 | }, | ||
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261 | "created": "2022-06-15T11:27:21.141541", | 238 | "created": "2022-06-15T11:27:21.141541", | ||
262 | "datastore_active": false, | 239 | "datastore_active": false, | ||
263 | "description": "VERSION 1.5. The world's most accurate | 240 | "description": "VERSION 1.5. The world's most accurate | ||
264 | population datasets. Seven maps/datasets for the distribution of | 241 | population datasets. Seven maps/datasets for the distribution of | ||
265 | various populations in Nigeria: (1) Overall population density (2) | 242 | various populations in Nigeria: (1) Overall population density (2) | ||
266 | Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) | 243 | Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) | ||
267 | Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).", | 244 | Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).", | ||
268 | "format": "", | 245 | "format": "", | ||
269 | "hash": "", | 246 | "hash": "", | ||
270 | "id": "d7c4dbb3-379f-45e8-8758-1ef1f81182c1", | 247 | "id": "d7c4dbb3-379f-45e8-8758-1ef1f81182c1", | ||
271 | "last_modified": null, | 248 | "last_modified": null, | ||
272 | "mimetype": null, | 249 | "mimetype": null, | ||
273 | "mimetype_inner": null, | 250 | "mimetype_inner": null, | ||
274 | "name": "Nigeria: high resolution population density maps", | 251 | "name": "Nigeria: high resolution population density maps", | ||
275 | "package_id": "fe17bb29-52c2-4029-af8e-58e4f362f956", | 252 | "package_id": "fe17bb29-52c2-4029-af8e-58e4f362f956", | ||
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279 | "size": null, | 256 | "size": null, | ||
280 | "state": "active", | 257 | "state": "active", | ||
281 | "url": | 258 | "url": | ||
282 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-nga", | 259 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-nga", | ||
283 | "url_type": null | 260 | "url_type": null | ||
284 | } | 261 | } | ||
285 | ], | 262 | ], | ||
286 | "revision_id": "9ca6a473-db23-4bf3-ad1d-cad6389f81e7", | 263 | "revision_id": "9ca6a473-db23-4bf3-ad1d-cad6389f81e7", | ||
287 | "state": "active", | 264 | "state": "active", | ||
288 | "tags": [ | 265 | "tags": [ | ||
289 | { | 266 | { | ||
290 | "display_name": "children", | 267 | "display_name": "children", | ||
291 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | 268 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | ||
292 | "name": "children", | 269 | "name": "children", | ||
293 | "state": "active", | 270 | "state": "active", | ||
294 | "vocabulary_id": null | 271 | "vocabulary_id": null | ||
295 | }, | 272 | }, | ||
296 | { | 273 | { | ||
297 | "display_name": "gender", | 274 | "display_name": "gender", | ||
298 | "id": "9923e71e-0c99-4abb-a0fa-5e7ccbc74956", | 275 | "id": "9923e71e-0c99-4abb-a0fa-5e7ccbc74956", | ||
299 | "name": "gender", | 276 | "name": "gender", | ||
300 | "state": "active", | 277 | "state": "active", | ||
301 | "vocabulary_id": null | 278 | "vocabulary_id": null | ||
302 | }, | 279 | }, | ||
303 | { | 280 | { | ||
304 | "display_name": "nigeria", | 281 | "display_name": "nigeria", | ||
305 | "id": "86671c58-04e8-4323-8904-b2b506740271", | 282 | "id": "86671c58-04e8-4323-8904-b2b506740271", | ||
306 | "name": "nigeria", | 283 | "name": "nigeria", | ||
307 | "state": "active", | 284 | "state": "active", | ||
308 | "vocabulary_id": null | 285 | "vocabulary_id": null | ||
309 | }, | 286 | }, | ||
310 | { | 287 | { | ||
311 | "display_name": "population", | 288 | "display_name": "population", | ||
312 | "id": "0020415a-6815-440e-96c9-b4e4a7b58464", | 289 | "id": "0020415a-6815-440e-96c9-b4e4a7b58464", | ||
313 | "name": "population", | 290 | "name": "population", | ||
314 | "state": "active", | 291 | "state": "active", | ||
315 | "vocabulary_id": null | 292 | "vocabulary_id": null | ||
316 | }, | 293 | }, | ||
317 | { | 294 | { | ||
318 | "display_name": "population density", | 295 | "display_name": "population density", | ||
319 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | 296 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | ||
320 | "name": "population density", | 297 | "name": "population density", | ||
321 | "state": "active", | 298 | "state": "active", | ||
322 | "vocabulary_id": null | 299 | "vocabulary_id": null | ||
323 | }, | 300 | }, | ||
324 | { | 301 | { | ||
325 | "display_name": "women", | 302 | "display_name": "women", | ||
326 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | 303 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | ||
327 | "name": "women", | 304 | "name": "women", | ||
328 | "state": "active", | 305 | "state": "active", | ||
329 | "vocabulary_id": null | 306 | "vocabulary_id": null | ||
330 | }, | 307 | }, | ||
331 | { | 308 | { | ||
332 | "display_name": "youth", | 309 | "display_name": "youth", | ||
333 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | 310 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | ||
334 | "name": "youth", | 311 | "name": "youth", | ||
335 | "state": "active", | 312 | "state": "active", | ||
336 | "vocabulary_id": null | 313 | "vocabulary_id": null | ||
337 | } | 314 | } | ||
338 | ], | 315 | ], | ||
339 | "title": "Nigeria: High Resolution Population Density Maps + | 316 | "title": "Nigeria: High Resolution Population Density Maps + | ||
340 | Demographic Estimates", | 317 | Demographic Estimates", | ||
341 | "type": "dataset", | 318 | "type": "dataset", | ||
342 | "url": | 319 | "url": | ||
343 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-nga", | 320 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-nga", | ||
344 | "version": "" | 321 | "version": "" | ||
345 | } | 322 | } |