Changes
On July 4, 2022, 14:51:44 (SAST), wasim:
-
Moved Somalia - Population Density from organization HDX - The Humanitarian Data Exchange to organization Open Cities Lab
f | 1 | { | f | 1 | { |
2 | "author": "WorldPop", | 2 | "author": "WorldPop", | ||
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": [], | ||
n | 6 | "groups": [], | n | 6 | "groups": [ |
7 | { | ||||
8 | "description": "The Humanitarian Data Exchange (HDX) is an open | ||||
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 | ||||
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 | ||||
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 | ||||
15 | responsible for bringing together humanitarian actors to ensure a | ||||
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 | ||||
18 | Africa.", | ||||
19 | "display_name": "HDX: Humanitarian Data Exchange", | ||||
20 | "id": "15791998-b8b5-41fa-841f-0393addadcbf", | ||||
21 | "image_display_url": | ||||
22 | "https://data.humdata.org/images/homepage/logo-hdx.svg", | ||||
23 | "name": "hdx-humanitarian-data-exchange", | ||||
24 | "title": "HDX: Humanitarian Data Exchange" | ||||
25 | }, | ||||
26 | { | ||||
27 | "description": "", | ||||
28 | "display_name": "Population ", | ||||
29 | "id": "ad455715-07fc-421f-aef4-780b25b9c67a", | ||||
30 | "image_display_url": "", | ||||
31 | "name": "population", | ||||
32 | "title": "Population " | ||||
33 | } | ||||
34 | ], | ||||
7 | "id": "c60c4435-86a2-4ee7-ac61-82beee007c46", | 35 | "id": "c60c4435-86a2-4ee7-ac61-82beee007c46", | ||
8 | "isopen": true, | 36 | "isopen": true, | ||
9 | "license_id": "cc-by", | 37 | "license_id": "cc-by", | ||
10 | "license_title": "Creative Commons Attribution", | 38 | "license_title": "Creative Commons Attribution", | ||
11 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 39 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
12 | "maintainer": "Brian O'Leary", | 40 | "maintainer": "Brian O'Leary", | ||
13 | "maintainer_email": "[email protected]", | 41 | "maintainer_email": "[email protected]", | ||
14 | "metadata_created": "2022-06-24T10:21:49.979503", | 42 | "metadata_created": "2022-06-24T10:21:49.979503", | ||
n | 15 | "metadata_modified": "2022-06-24T10:23:41.708344", | n | 43 | "metadata_modified": "2022-07-04T12:51:44.676724", |
16 | "name": "somalia-population-density", | 44 | "name": "somalia-population-density", | ||
17 | "notes": "WorldPop produces different types of gridded population | 45 | "notes": "WorldPop produces different types of gridded population | ||
18 | count datasets, depending on the methods used and end application. | 46 | count datasets, depending on the methods used and end application. | ||
19 | \r\n\r\nDatasets are available to download in Geotiff and ASCII XYZ | 47 | \r\n\r\nDatasets are available to download in Geotiff and ASCII XYZ | ||
20 | format at a resolution of 30 arc-seconds (approximately 1km at the | 48 | format at a resolution of 30 arc-seconds (approximately 1km at the | ||
21 | equator)\r\n\r\n-Unconstrained individual countries 2000-2020: | 49 | equator)\r\n\r\n-Unconstrained individual countries 2000-2020: | ||
22 | Population density datasets for all countries of the World for each | 50 | Population density datasets for all countries of the World for each | ||
23 | year 2000-2020 \u2013 derived from the corresponding Unconstrained | 51 | year 2000-2020 \u2013 derived from the corresponding Unconstrained | ||
24 | individual countries 2000-2020 population count datasets by dividing | 52 | individual countries 2000-2020 population count datasets by dividing | ||
25 | the number of people in each pixel by the pixel surface area. These | 53 | the number of people in each pixel by the pixel surface area. These | ||
26 | are produced using the unconstrained top-down modelling | 54 | are produced using the unconstrained top-down modelling | ||
27 | method.\r\n\r\n-Unconstrained individual countries 2000-2020 UN | 55 | method.\r\n\r\n-Unconstrained individual countries 2000-2020 UN | ||
28 | adjusted: Population density datasets for all countries of the World | 56 | adjusted: Population density datasets for all countries of the World | ||
29 | for each year 2000-2020 \u2013 derived from the corresponding | 57 | for each year 2000-2020 \u2013 derived from the corresponding | ||
30 | Unconstrained individual countries 2000-2020 population UN adjusted | 58 | Unconstrained individual countries 2000-2020 population UN adjusted | ||
31 | count datasets by dividing the number of people in each pixel, | 59 | count datasets by dividing the number of people in each pixel, | ||
32 | adjusted to match the country total from the official United Nations | 60 | adjusted to match the country total from the official United Nations | ||
33 | population estimates (UN 2019), by the pixel surface area. These are | 61 | population estimates (UN 2019), by the pixel surface area. These are | ||
34 | produced using the unconstrained top-down modelling | 62 | produced using the unconstrained top-down modelling | ||
35 | method.\r\n\r\nData for earlier dates is available directly from | 63 | method.\r\n\r\nData for earlier dates is available directly from | ||
36 | WorldPop.\r\n\r\nWorldPop (www.worldpop.org - School of Geography and | 64 | WorldPop.\r\n\r\nWorldPop (www.worldpop.org - School of Geography and | ||
37 | Environmental Science, University of Southampton; Department of | 65 | Environmental Science, University of Southampton; Department of | ||
38 | Geography and Geosciences, University of Louisville; Departement de | 66 | Geography and Geosciences, University of Louisville; Departement de | ||
39 | Geographie, Universite de Namur) and Center for International Earth | 67 | Geographie, Universite de Namur) and Center for International Earth | ||
40 | Science Information Network (CIESIN), Columbia University (2018). | 68 | Science Information Network (CIESIN), Columbia University (2018). | ||
41 | Global High Resolution Population Denominators Project - Funded by The | 69 | Global High Resolution Population Denominators Project - Funded by The | ||
42 | Bill and Melinda Gates Foundation (OPP1134076). | 70 | Bill and Melinda Gates Foundation (OPP1134076). | ||
43 | https://dx.doi.org/10.5258/SOTON/WP00674", | 71 | https://dx.doi.org/10.5258/SOTON/WP00674", | ||
44 | "num_resources": 1, | 72 | "num_resources": 1, | ||
45 | "num_tags": 4, | 73 | "num_tags": 4, | ||
46 | "organization": { | 74 | "organization": { | ||
47 | "approval_status": "approved", | 75 | "approval_status": "approved", | ||
n | 48 | "created": "2022-06-15T09:44:22.871262", | n | 76 | "created": "2022-07-04T08:06:45.420882", |
49 | "description": "The Humanitarian Data Exchange (HDX) is an open | 77 | "description": "We work to build inclusion and participatory | ||
50 | platform for sharing data across crises and organisations. Launched in | 78 | democracy in cities and urban spaces through empowering citizens, | ||
51 | July 2014, the goal of HDX is to make humanitarian data easy to find | 79 | building trust and accountability in civic space, and capacitating | ||
52 | and use for analysis. Our growing collection of datasets has been | 80 | government. You can find our website | ||
53 | accessed by users in over 200 countries and territories.\r\n\r\nHDX is | 81 | [here](https://opencitieslab.org/).", | ||
54 | managed by OCHA's Centre for Humanitarian Data, which is located in | 82 | "id": "8e526815-d516-4f6c-9ae0-a4d62555c30c", | ||
55 | The Hague. OCHA is part of the United Nations Secretariat and is | ||||
56 | responsible for bringing together humanitarian actors to ensure a | ||||
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 | ||||
59 | Africa.", | ||||
60 | "id": "ad11db0c-27d3-433d-bc99-973c2ffae709", | ||||
61 | "image_url": | 83 | "image_url": | ||
n | 62 | "https://data.humdata.org/images/homepage/logo-hdx.svg", | n | 84 | ttps://opencitieslab.org/odd/static/dist/img/ocl_logo_header-nav.png", |
63 | "is_organization": true, | 85 | "is_organization": true, | ||
n | 64 | "name": "hdx-the-humanitarian-data-exchange", | n | 86 | "name": "open-cities-lab", |
65 | "revision_id": "e6c349dd-82c3-4176-a1c7-a4d89d8eae93", | 87 | "revision_id": "35e0d462-e6b8-4c18-8743-e9361e136009", | ||
66 | "state": "active", | 88 | "state": "active", | ||
n | 67 | "title": "HDX - The Humanitarian Data Exchange", | n | 89 | "title": "Open Cities Lab", |
68 | "type": "organization" | 90 | "type": "organization" | ||
69 | }, | 91 | }, | ||
n | 70 | "owner_org": "ad11db0c-27d3-433d-bc99-973c2ffae709", | n | 92 | "owner_org": "8e526815-d516-4f6c-9ae0-a4d62555c30c", |
71 | "private": false, | 93 | "private": false, | ||
72 | "relationships_as_object": [], | 94 | "relationships_as_object": [], | ||
73 | "relationships_as_subject": [], | 95 | "relationships_as_subject": [], | ||
74 | "resources": [ | 96 | "resources": [ | ||
75 | { | 97 | { | ||
76 | "cache_last_updated": null, | 98 | "cache_last_updated": null, | ||
77 | "cache_url": null, | 99 | "cache_url": null, | ||
78 | "created": "2022-06-24T10:23:19.730685", | 100 | "created": "2022-06-24T10:23:19.730685", | ||
79 | "datastore_active": false, | 101 | "datastore_active": false, | ||
80 | "description": "WorldPop produces different types of gridded | 102 | "description": "WorldPop produces different types of gridded | ||
81 | population count datasets, depending on the methods used and end | 103 | population count datasets, depending on the methods used and end | ||
82 | application. \r\n\r\nDatasets are available to download in Geotiff and | 104 | application. \r\n\r\nDatasets are available to download in Geotiff and | ||
83 | ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km | 105 | ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km | ||
84 | at the equator)\r\n\r\n-Unconstrained individual countries 2000-2020: | 106 | at the equator)\r\n\r\n-Unconstrained individual countries 2000-2020: | ||
85 | Population density datasets for all countries of the World for each | 107 | Population density datasets for all countries of the World for each | ||
86 | year 2000-2020 \u2013 derived from the corresponding Unconstrained | 108 | year 2000-2020 \u2013 derived from the corresponding Unconstrained | ||
87 | individual countries 2000-2020 population count datasets by dividing | 109 | individual countries 2000-2020 population count datasets by dividing | ||
88 | the number of people in each pixel by the pixel surface area. These | 110 | the number of people in each pixel by the pixel surface area. These | ||
89 | are produced using the unconstrained top-down modelling | 111 | are produced using the unconstrained top-down modelling | ||
90 | method.\r\n\r\n-Unconstrained individual countries 2000-2020 UN | 112 | method.\r\n\r\n-Unconstrained individual countries 2000-2020 UN | ||
91 | adjusted: Population density datasets for all countries of the World | 113 | adjusted: Population density datasets for all countries of the World | ||
92 | for each year 2000-2020 \u2013 derived from the corresponding | 114 | for each year 2000-2020 \u2013 derived from the corresponding | ||
93 | Unconstrained individual countries 2000-2020 population UN adjusted | 115 | Unconstrained individual countries 2000-2020 population UN adjusted | ||
94 | count datasets by dividing the number of people in each pixel, | 116 | count datasets by dividing the number of people in each pixel, | ||
95 | adjusted to match the country total from the official United Nations | 117 | adjusted to match the country total from the official United Nations | ||
96 | population estimates (UN 2019), by the pixel surface area. These are | 118 | population estimates (UN 2019), by the pixel surface area. These are | ||
97 | produced using the unconstrained top-down modelling | 119 | produced using the unconstrained top-down modelling | ||
98 | method.\r\n\r\nData for earlier dates is available directly from | 120 | method.\r\n\r\nData for earlier dates is available directly from | ||
99 | WorldPop.\r\n\r\nWorldPop (www.worldpop.org - School of Geography and | 121 | WorldPop.\r\n\r\nWorldPop (www.worldpop.org - School of Geography and | ||
100 | Environmental Science, University of Southampton; Department of | 122 | Environmental Science, University of Southampton; Department of | ||
101 | Geography and Geosciences, University of Louisville; Departement de | 123 | Geography and Geosciences, University of Louisville; Departement de | ||
102 | Geographie, Universite de Namur) and Center for International Earth | 124 | Geographie, Universite de Namur) and Center for International Earth | ||
103 | Science Information Network (CIESIN), Columbia University (2018). | 125 | Science Information Network (CIESIN), Columbia University (2018). | ||
104 | Global High Resolution Population Denominators Project - Funded by The | 126 | Global High Resolution Population Denominators Project - Funded by The | ||
105 | Bill and Melinda Gates Foundation (OPP1134076). | 127 | Bill and Melinda Gates Foundation (OPP1134076). | ||
106 | https://dx.doi.org/10.5258/SOTON/WP00674", | 128 | https://dx.doi.org/10.5258/SOTON/WP00674", | ||
107 | "format": "", | 129 | "format": "", | ||
108 | "hash": "", | 130 | "hash": "", | ||
109 | "id": "60ff6df3-5012-40c7-b11a-2609e53f8583", | 131 | "id": "60ff6df3-5012-40c7-b11a-2609e53f8583", | ||
110 | "last_modified": null, | 132 | "last_modified": null, | ||
111 | "mimetype": null, | 133 | "mimetype": null, | ||
112 | "mimetype_inner": null, | 134 | "mimetype_inner": null, | ||
113 | "name": "Somalia - Population Density", | 135 | "name": "Somalia - Population Density", | ||
114 | "package_id": "c60c4435-86a2-4ee7-ac61-82beee007c46", | 136 | "package_id": "c60c4435-86a2-4ee7-ac61-82beee007c46", | ||
115 | "position": 0, | 137 | "position": 0, | ||
116 | "resource_type": null, | 138 | "resource_type": null, | ||
117 | "revision_id": "8d7f8d82-5814-4fe8-a983-67c2f42be523", | 139 | "revision_id": "8d7f8d82-5814-4fe8-a983-67c2f42be523", | ||
118 | "size": null, | 140 | "size": null, | ||
119 | "state": "active", | 141 | "state": "active", | ||
120 | "url": | 142 | "url": | ||
121 | s://data.humdata.org/dataset/worldpop-population-density-for-somalia", | 143 | s://data.humdata.org/dataset/worldpop-population-density-for-somalia", | ||
122 | "url_type": null | 144 | "url_type": null | ||
123 | } | 145 | } | ||
124 | ], | 146 | ], | ||
t | 125 | "revision_id": "21f4dbba-840d-419b-b1ca-8f2fc1464769", | t | 147 | "revision_id": "885095cd-3a08-4015-a6a6-1fb6d5c4bd1f", |
126 | "state": "active", | 148 | "state": "active", | ||
127 | "tags": [ | 149 | "tags": [ | ||
128 | { | 150 | { | ||
129 | "display_name": "Sudan", | 151 | "display_name": "Sudan", | ||
130 | "id": "6942cfd8-178c-43ce-b3e4-07993c79824c", | 152 | "id": "6942cfd8-178c-43ce-b3e4-07993c79824c", | ||
131 | "name": "Sudan", | 153 | "name": "Sudan", | ||
132 | "state": "active", | 154 | "state": "active", | ||
133 | "vocabulary_id": null | 155 | "vocabulary_id": null | ||
134 | }, | 156 | }, | ||
135 | { | 157 | { | ||
136 | "display_name": "population count", | 158 | "display_name": "population count", | ||
137 | "id": "f7228262-21a4-4fe5-a713-f43c29367f23", | 159 | "id": "f7228262-21a4-4fe5-a713-f43c29367f23", | ||
138 | "name": "population count", | 160 | "name": "population count", | ||
139 | "state": "active", | 161 | "state": "active", | ||
140 | "vocabulary_id": null | 162 | "vocabulary_id": null | ||
141 | }, | 163 | }, | ||
142 | { | 164 | { | ||
143 | "display_name": "population density", | 165 | "display_name": "population density", | ||
144 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | 166 | "id": "98311ff5-1cea-4f34-92fb-c0757c6ce5ca", | ||
145 | "name": "population density", | 167 | "name": "population density", | ||
146 | "state": "active", | 168 | "state": "active", | ||
147 | "vocabulary_id": null | 169 | "vocabulary_id": null | ||
148 | }, | 170 | }, | ||
149 | { | 171 | { | ||
150 | "display_name": "population mapping", | 172 | "display_name": "population mapping", | ||
151 | "id": "5a75e952-d82b-44e3-8152-e0408a3cb3e3", | 173 | "id": "5a75e952-d82b-44e3-8152-e0408a3cb3e3", | ||
152 | "name": "population mapping", | 174 | "name": "population mapping", | ||
153 | "state": "active", | 175 | "state": "active", | ||
154 | "vocabulary_id": null | 176 | "vocabulary_id": null | ||
155 | } | 177 | } | ||
156 | ], | 178 | ], | ||
157 | "title": "Somalia - Population Density", | 179 | "title": "Somalia - Population Density", | ||
158 | "type": "dataset", | 180 | "type": "dataset", | ||
159 | "url": | 181 | "url": | ||
160 | s://data.humdata.org/dataset/worldpop-population-density-for-somalia", | 182 | s://data.humdata.org/dataset/worldpop-population-density-for-somalia", | ||
161 | "version": "" | 183 | "version": "" | ||
162 | } | 184 | } |