ለውጦች
On ሰኔ 27, 2022, 17:42:36 (SAST),
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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": "77d79e63-5fb4-4320-94e4-51e5e9b8031c", | 4 | "creator_user_id": "77d79e63-5fb4-4320-94e4-51e5e9b8031c", | ||
5 | "extras": [], | 5 | "extras": [], | ||
6 | "groups": [], | 6 | "groups": [], | ||
7 | "id": "18b5ee0a-602f-4484-a1ee-4181524deb45", | 7 | "id": "18b5ee0a-602f-4484-a1ee-4181524deb45", | ||
8 | "isopen": true, | 8 | "isopen": true, | ||
9 | "license_id": "cc-by", | 9 | "license_id": "cc-by", | ||
10 | "license_title": "Creative Commons Attribution", | 10 | "license_title": "Creative Commons Attribution", | ||
11 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 11 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
12 | "maintainer": "Brian O'Leary", | 12 | "maintainer": "Brian O'Leary", | ||
13 | "maintainer_email": "[email protected]", | 13 | "maintainer_email": "[email protected]", | ||
14 | "metadata_created": "2022-06-27T15:41:26.792237", | 14 | "metadata_created": "2022-06-27T15:41:26.792237", | ||
n | 15 | "metadata_modified": "2022-06-27T15:42:35.691305", | n | 15 | "metadata_modified": "2022-06-27T15:42:35.890528", |
16 | "name": | 16 | "name": | ||
17 | -congo-high-resolution-population-density-maps-demographic-estimates", | 17 | -congo-high-resolution-population-density-maps-demographic-estimates", | ||
18 | "notes": "The world's most accurate population datasets. Seven | 18 | "notes": "The world's most accurate population datasets. Seven | ||
19 | maps/datasets for the distribution of various populations in | 19 | maps/datasets for the distribution of various populations in | ||
20 | Democratic Republic of the Congo: (1) Overall population density (2) | 20 | Democratic Republic of the Congo: (1) Overall population density (2) | ||
21 | Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) | 21 | Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) | ||
22 | Elderly (ages 60+) (7) Women of reproductive age (ages | 22 | Elderly (ages 60+) (7) Women of reproductive age (ages | ||
23 | 15-49).\r\n\r\n### Methodology\r\n\r\nThese high-resolution maps are | 23 | 15-49).\r\n\r\n### Methodology\r\n\r\nThese high-resolution maps are | ||
24 | created using machine learning techniques to identify buildings from | 24 | created using machine learning techniques to identify buildings from | ||
25 | commercially available satellite images. This is then overlayed with | 25 | commercially available satellite images. This is then overlayed with | ||
26 | general population estimates based on publicly available census data | 26 | general population estimates based on publicly available census data | ||
27 | and other population statistics at Columbia University. The resulting | 27 | and other population statistics at Columbia University. The resulting | ||
28 | maps are the most detailed and actionable tools available for aid and | 28 | maps are the most detailed and actionable tools available for aid and | ||
29 | research organizations. For more information about the methodology | 29 | research organizations. For more information about the methodology | ||
30 | used to create our high resolution population density maps and the | 30 | used to create our high resolution population density maps and the | ||
31 | demographic distributions, click | 31 | demographic distributions, click | ||
32 | resolution-population-density-maps-demographic-estimates/).\r\n\r\nFor | 32 | resolution-population-density-maps-demographic-estimates/).\r\n\r\nFor | ||
33 | information about how to use HDX to access these datasets, please | 33 | information about how to use HDX to access these datasets, please | ||
34 | visit: | 34 | visit: | ||
35 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | 35 | n-density-maps-demographic-estimates-documentation/\r\n\r\nAdjustments | ||
36 | to match the census population with the UN estimates are applied at | 36 | to match the census population with the UN estimates are applied at | ||
37 | the national level. The UN estimate for a given country (or | 37 | the national level. The UN estimate for a given country (or | ||
38 | state/territory) is divided by the total census estimate of population | 38 | state/territory) is divided by the total census estimate of population | ||
39 | for the given country. The resulting adjustment factor is multiplied | 39 | for the given country. The resulting adjustment factor is multiplied | ||
40 | by each administrative unit census value for the target year. This | 40 | by each administrative unit census value for the target year. This | ||
41 | preserves the relative population totals across administrative units | 41 | preserves the relative population totals across administrative units | ||
42 | while matching the UN total. More information can be found | 42 | while matching the UN total. More information can be found | ||
43 | ocs/census-information-for-high-resolution-population-density-maps/)", | 43 | ocs/census-information-for-high-resolution-population-density-maps/)", | ||
44 | "num_resources": 1, | 44 | "num_resources": 1, | ||
45 | "num_tags": 4, | 45 | "num_tags": 4, | ||
46 | "organization": { | 46 | "organization": { | ||
47 | "approval_status": "approved", | 47 | "approval_status": "approved", | ||
48 | "created": "2022-06-15T09:44:22.871262", | 48 | "created": "2022-06-15T09:44:22.871262", | ||
49 | "description": "The Humanitarian Data Exchange (HDX) is an open | 49 | "description": "The Humanitarian Data Exchange (HDX) is an open | ||
50 | platform for sharing data across crises and organisations. Launched in | 50 | platform for sharing data across crises and organisations. Launched in | ||
51 | July 2014, the goal of HDX is to make humanitarian data easy to find | 51 | July 2014, the goal of HDX is to make humanitarian data easy to find | ||
52 | and use for analysis. Our growing collection of datasets has been | 52 | and use for analysis. Our growing collection of datasets has been | ||
53 | accessed by users in over 200 countries and territories.\r\n\r\nHDX is | 53 | accessed by users in over 200 countries and territories.\r\n\r\nHDX is | ||
54 | managed by OCHA's Centre for Humanitarian Data, which is located in | 54 | managed by OCHA's Centre for Humanitarian Data, which is located in | ||
55 | The Hague. OCHA is part of the United Nations Secretariat and is | 55 | The Hague. OCHA is part of the United Nations Secretariat and is | ||
56 | responsible for bringing together humanitarian actors to ensure a | 56 | responsible for bringing together humanitarian actors to ensure a | ||
57 | coherent response to emergencies. The HDX team includes OCHA staff and | 57 | coherent response to emergencies. The HDX team includes OCHA staff and | ||
58 | a number of consultants who are based in North America, Europe and | 58 | a number of consultants who are based in North America, Europe and | ||
59 | Africa.", | 59 | Africa.", | ||
60 | "id": "ad11db0c-27d3-433d-bc99-973c2ffae709", | 60 | "id": "ad11db0c-27d3-433d-bc99-973c2ffae709", | ||
61 | "image_url": | 61 | "image_url": | ||
62 | "https://data.humdata.org/images/homepage/logo-hdx.svg", | 62 | "https://data.humdata.org/images/homepage/logo-hdx.svg", | ||
63 | "is_organization": true, | 63 | "is_organization": true, | ||
64 | "name": "hdx-the-humanitarian-data-exchange", | 64 | "name": "hdx-the-humanitarian-data-exchange", | ||
65 | "revision_id": "e6c349dd-82c3-4176-a1c7-a4d89d8eae93", | 65 | "revision_id": "e6c349dd-82c3-4176-a1c7-a4d89d8eae93", | ||
66 | "state": "active", | 66 | "state": "active", | ||
67 | "title": "HDX - The Humanitarian Data Exchange", | 67 | "title": "HDX - The Humanitarian Data Exchange", | ||
68 | "type": "organization" | 68 | "type": "organization" | ||
69 | }, | 69 | }, | ||
70 | "owner_org": "ad11db0c-27d3-433d-bc99-973c2ffae709", | 70 | "owner_org": "ad11db0c-27d3-433d-bc99-973c2ffae709", | ||
71 | "private": false, | 71 | "private": false, | ||
72 | "relationships_as_object": [], | 72 | "relationships_as_object": [], | ||
73 | "relationships_as_subject": [], | 73 | "relationships_as_subject": [], | ||
74 | "resources": [ | 74 | "resources": [ | ||
75 | { | 75 | { | ||
76 | "cache_last_updated": null, | 76 | "cache_last_updated": null, | ||
77 | "cache_url": null, | 77 | "cache_url": null, | ||
78 | "created": "2022-06-27T15:42:35.711632", | 78 | "created": "2022-06-27T15:42:35.711632", | ||
79 | "datastore_active": false, | 79 | "datastore_active": false, | ||
80 | "description": "The world's most accurate population datasets. | 80 | "description": "The world's most accurate population datasets. | ||
81 | Seven maps/datasets for the distribution of various populations in the | 81 | Seven maps/datasets for the distribution of various populations in the | ||
82 | Democratic Republic of Congo: (1) Overall population density (2) Women | 82 | Democratic Republic of Congo: (1) Overall population density (2) Women | ||
83 | (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly | 83 | (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly | ||
84 | (ages 60+) (7) Women of reproductive age (ages 15-49).", | 84 | (ages 60+) (7) Women of reproductive age (ages 15-49).", | ||
85 | "format": "", | 85 | "format": "", | ||
86 | "hash": "", | 86 | "hash": "", | ||
87 | "id": "6c55fe72-73e8-4950-8c13-d736ae0d2e7e", | 87 | "id": "6c55fe72-73e8-4950-8c13-d736ae0d2e7e", | ||
88 | "last_modified": null, | 88 | "last_modified": null, | ||
89 | "mimetype": null, | 89 | "mimetype": null, | ||
90 | "mimetype_inner": null, | 90 | "mimetype_inner": null, | ||
91 | "name": "Democratic Republic of the Congo: High Resolution | 91 | "name": "Democratic Republic of the Congo: High Resolution | ||
92 | Population Density Maps + Demographic Estimates", | 92 | Population Density Maps + Demographic Estimates", | ||
93 | "package_id": "18b5ee0a-602f-4484-a1ee-4181524deb45", | 93 | "package_id": "18b5ee0a-602f-4484-a1ee-4181524deb45", | ||
94 | "position": 0, | 94 | "position": 0, | ||
95 | "resource_type": null, | 95 | "resource_type": null, | ||
n | 96 | "revision_id": "9c88492e-4f62-40f8-bfa2-1b58e57971ff", | n | 96 | "revision_id": "2a61e7d2-8101-4b76-aa82-f08a7436e8ae", |
97 | "size": null, | 97 | "size": null, | ||
98 | "state": "active", | 98 | "state": "active", | ||
99 | "url": | 99 | "url": | ||
100 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-cod", | 100 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-cod", | ||
101 | "url_type": null | 101 | "url_type": null | ||
102 | } | 102 | } | ||
103 | ], | 103 | ], | ||
t | 104 | "revision_id": "e1979555-fb34-4ec0-b757-e0eadf9f2607", | t | 104 | "revision_id": "2a61e7d2-8101-4b76-aa82-f08a7436e8ae", |
105 | "state": "draft", | 105 | "state": "active", | ||
106 | "tags": [ | 106 | "tags": [ | ||
107 | { | 107 | { | ||
108 | "display_name": "Democratic Republic of the Congo", | 108 | "display_name": "Democratic Republic of the Congo", | ||
109 | "id": "61d1fc15-f5df-4925-9504-b53183863189", | 109 | "id": "61d1fc15-f5df-4925-9504-b53183863189", | ||
110 | "name": "Democratic Republic of the Congo", | 110 | "name": "Democratic Republic of the Congo", | ||
111 | "state": "active", | 111 | "state": "active", | ||
112 | "vocabulary_id": null | 112 | "vocabulary_id": null | ||
113 | }, | 113 | }, | ||
114 | { | 114 | { | ||
115 | "display_name": "population count", | 115 | "display_name": "population count", | ||
116 | "id": "f7228262-21a4-4fe5-a713-f43c29367f23", | 116 | "id": "f7228262-21a4-4fe5-a713-f43c29367f23", | ||
117 | "name": "population count", | 117 | "name": "population count", | ||
118 | "state": "active", | 118 | "state": "active", | ||
119 | "vocabulary_id": null | 119 | "vocabulary_id": null | ||
120 | }, | 120 | }, | ||
121 | { | 121 | { | ||
122 | "display_name": "population density", | 122 | "display_name": "population density", | ||
123 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | 123 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | ||
124 | "name": "population density", | 124 | "name": "population density", | ||
125 | "state": "active", | 125 | "state": "active", | ||
126 | "vocabulary_id": null | 126 | "vocabulary_id": null | ||
127 | }, | 127 | }, | ||
128 | { | 128 | { | ||
129 | "display_name": "population mapping", | 129 | "display_name": "population mapping", | ||
130 | "id": "5a75e952-d82b-44e3-8152-e0408a3cb3e3", | 130 | "id": "5a75e952-d82b-44e3-8152-e0408a3cb3e3", | ||
131 | "name": "population mapping", | 131 | "name": "population mapping", | ||
132 | "state": "active", | 132 | "state": "active", | ||
133 | "vocabulary_id": null | 133 | "vocabulary_id": null | ||
134 | } | 134 | } | ||
135 | ], | 135 | ], | ||
136 | "title": "Democratic Republic of the Congo: High Resolution | 136 | "title": "Democratic Republic of the Congo: High Resolution | ||
137 | Population Density Maps + Demographic Estimates", | 137 | Population Density Maps + Demographic Estimates", | ||
138 | "type": "dataset", | 138 | "type": "dataset", | ||
139 | "url": | 139 | "url": | ||
140 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-cod", | 140 | s://data.humdata.org/dataset/highresolutionpopulationdensitymaps-cod", | ||
141 | "version": "" | 141 | "version": "" | ||
142 | } | 142 | } |