Changes
On June 14, 2023, 11:18:37 (SAST),
Brian O'Leary:
-
Deleted resource sen_youth_15_24_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": "2023-06-14T09:18:17.898160", | n | 43 | "metadata_modified": "2023-06-14T09:18:37.170480", |
| 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": 3, | n | 72 | "num_resources": 2, |
| 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": [], | ||
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| 147 | "datastore_active": false, | 124 | "datastore_active": false, | ||
| 148 | "description": "The world's most accurate population datasets. | 125 | "description": "The world's most accurate population datasets. | ||
| 149 | Seven maps/datasets for the distribution of various populations in | 126 | Seven maps/datasets for the distribution of various populations in | ||
| 150 | Senegal: (1) Overall population density (2) Women (3) Men (4) Children | 127 | Senegal: (1) Overall population density (2) Women (3) Men (4) Children | ||
| 151 | (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of | 128 | (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of | ||
| 152 | reproductive age (ages 15-49).", | 129 | reproductive age (ages 15-49).", | ||
| 153 | "format": "", | 130 | "format": "", | ||
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| 159 | "name": "Senegal high resolution population density maps ", | 136 | "name": "Senegal high resolution population density maps ", | ||
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| 164 | "size": null, | 141 | "size": null, | ||
| 165 | "state": "active", | 142 | "state": "active", | ||
| 166 | "url": | 143 | "url": | ||
| 167 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-sen", | 144 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-sen", | ||
| 168 | "url_type": null | 145 | "url_type": null | ||
| 169 | } | 146 | } | ||
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| 172 | "state": "active", | 149 | "state": "active", | ||
| 173 | "tags": [ | 150 | "tags": [ | ||
| 174 | { | 151 | { | ||
| 175 | "display_name": "children", | 152 | "display_name": "children", | ||
| 176 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | 153 | "id": "a31aa94e-cdbe-470b-b953-602bfc01eeab", | ||
| 177 | "name": "children", | 154 | "name": "children", | ||
| 178 | "state": "active", | 155 | "state": "active", | ||
| 179 | "vocabulary_id": null | 156 | "vocabulary_id": null | ||
| 180 | }, | 157 | }, | ||
| 181 | { | 158 | { | ||
| 182 | "display_name": "elderly", | 159 | "display_name": "elderly", | ||
| 183 | "id": "9c11b077-a76b-4a95-b6ee-afb6c112f48c", | 160 | "id": "9c11b077-a76b-4a95-b6ee-afb6c112f48c", | ||
| 184 | "name": "elderly", | 161 | "name": "elderly", | ||
| 185 | "state": "active", | 162 | "state": "active", | ||
| 186 | "vocabulary_id": null | 163 | "vocabulary_id": null | ||
| 187 | }, | 164 | }, | ||
| 188 | { | 165 | { | ||
| 189 | "display_name": "population density", | 166 | "display_name": "population density", | ||
| 190 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | 167 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | ||
| 191 | "name": "population density", | 168 | "name": "population density", | ||
| 192 | "state": "active", | 169 | "state": "active", | ||
| 193 | "vocabulary_id": null | 170 | "vocabulary_id": null | ||
| 194 | }, | 171 | }, | ||
| 195 | { | 172 | { | ||
| 196 | "display_name": "senegal", | 173 | "display_name": "senegal", | ||
| 197 | "id": "a044a0a6-098c-4aa9-a828-14462af6be1b", | 174 | "id": "a044a0a6-098c-4aa9-a828-14462af6be1b", | ||
| 198 | "name": "senegal", | 175 | "name": "senegal", | ||
| 199 | "state": "active", | 176 | "state": "active", | ||
| 200 | "vocabulary_id": null | 177 | "vocabulary_id": null | ||
| 201 | }, | 178 | }, | ||
| 202 | { | 179 | { | ||
| 203 | "display_name": "women", | 180 | "display_name": "women", | ||
| 204 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | 181 | "id": "d8f22a99-abe8-41cb-ae9c-4b543eee7cdf", | ||
| 205 | "name": "women", | 182 | "name": "women", | ||
| 206 | "state": "active", | 183 | "state": "active", | ||
| 207 | "vocabulary_id": null | 184 | "vocabulary_id": null | ||
| 208 | }, | 185 | }, | ||
| 209 | { | 186 | { | ||
| 210 | "display_name": "women of reproductive age", | 187 | "display_name": "women of reproductive age", | ||
| 211 | "id": "a1f9dfb8-316b-40bd-8182-5e3afdf9237c", | 188 | "id": "a1f9dfb8-316b-40bd-8182-5e3afdf9237c", | ||
| 212 | "name": "women of reproductive age", | 189 | "name": "women of reproductive age", | ||
| 213 | "state": "active", | 190 | "state": "active", | ||
| 214 | "vocabulary_id": null | 191 | "vocabulary_id": null | ||
| 215 | }, | 192 | }, | ||
| 216 | { | 193 | { | ||
| 217 | "display_name": "youth", | 194 | "display_name": "youth", | ||
| 218 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | 195 | "id": "98ff881a-a277-4d3a-9641-7657ad12e6a7", | ||
| 219 | "name": "youth", | 196 | "name": "youth", | ||
| 220 | "state": "active", | 197 | "state": "active", | ||
| 221 | "vocabulary_id": null | 198 | "vocabulary_id": null | ||
| 222 | } | 199 | } | ||
| 223 | ], | 200 | ], | ||
| 224 | "title": "Senegal: High Resolution Population Density Maps + | 201 | "title": "Senegal: High Resolution Population Density Maps + | ||
| 225 | Demographic Estimates", | 202 | Demographic Estimates", | ||
| 226 | "type": "dataset", | 203 | "type": "dataset", | ||
| 227 | "url": | 204 | "url": | ||
| 228 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-sen", | 205 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-sen", | ||
| 229 | "version": "" | 206 | "version": "" | ||
| 230 | } | 207 | } |