Perubahan
On 5 Oktober 2022 16.26.43 UTC, Richard Hůlek:
-
Added resource GMP2 Data Warehouse Africa Region - WFS to GMP2: Africa Region
f | 1 | { | f | 1 | { |
2 | "author": "Vincent Odongo Madadi, Principal investigator, ROG | 2 | "author": "Vincent Odongo Madadi, Principal investigator, ROG | ||
3 | Africa", | 3 | Africa", | ||
4 | "author_email": "vmadadi@uonbi.ac.ke", | 4 | "author_email": "vmadadi@uonbi.ac.ke", | ||
5 | "creator_user_id": "dff6eb9e-b1ae-4b87-ad44-10b9740f5faf", | 5 | "creator_user_id": "dff6eb9e-b1ae-4b87-ad44-10b9740f5faf", | ||
6 | "extras": [ | 6 | "extras": [ | ||
7 | { | 7 | { | ||
8 | "key": "Chemical compound", | 8 | "key": "Chemical compound", | ||
9 | "value": "PFOS, PCB" | 9 | "value": "PFOS, PCB" | ||
10 | }, | 10 | }, | ||
11 | { | 11 | { | ||
12 | "key": "Chemical parameter", | 12 | "key": "Chemical parameter", | ||
13 | "value": "Aldrin, Alpha-hexachlorocyclohexane (\u03b1-HCH), | 13 | "value": "Aldrin, Alpha-hexachlorocyclohexane (\u03b1-HCH), | ||
14 | Beta-hexachlorocyclohexane (\u03b2-HCH), Chlordane, | 14 | Beta-hexachlorocyclohexane (\u03b2-HCH), Chlordane, | ||
15 | Dichlorodiphenyltrichloroethane (DDT), Dieldrin, Endosulfan, Endrin, | 15 | Dichlorodiphenyltrichloroethane (DDT), Dieldrin, Endosulfan, Endrin, | ||
16 | Gamma-hexachlorocyclohexane (\u03b3-HCH), Heptachlor, | 16 | Gamma-hexachlorocyclohexane (\u03b3-HCH), Heptachlor, | ||
17 | Hexabromobiphenyl (HBB), Hexabromocyclododecane (HBCD), | 17 | Hexabromobiphenyl (HBB), Hexabromocyclododecane (HBCD), | ||
18 | Hexachlorobenzene (HCB), Mirex, Pentachlorobenzene (PeCBz), | 18 | Hexachlorobenzene (HCB), Mirex, Pentachlorobenzene (PeCBz), | ||
19 | Perfluorooctane sulfonic acid (PFOS), Polybromodiphenyl ethers (PBDE), | 19 | Perfluorooctane sulfonic acid (PFOS), Polybromodiphenyl ethers (PBDE), | ||
20 | Polychlorinated biphenyls (dl-PCB) \u2013 coplanar, Polychlorinated | 20 | Polychlorinated biphenyls (dl-PCB) \u2013 coplanar, Polychlorinated | ||
21 | biphenyls (PCB) \u2013 indicator, Polychlorinated | 21 | biphenyls (PCB) \u2013 indicator, Polychlorinated | ||
22 | dibenzodioxins/dibenzofurans (PCDD/F), Toxaphene, Polychlorinated | 22 | dibenzodioxins/dibenzofurans (PCDD/F), Toxaphene, Polychlorinated | ||
23 | dibenzofurans (PCDF), Polychlorinated dibenzodioxins (PCDD)" | 23 | dibenzofurans (PCDF), Polychlorinated dibenzodioxins (PCDD)" | ||
24 | }, | 24 | }, | ||
25 | { | 25 | { | ||
26 | "key": "Country", | 26 | "key": "Country", | ||
27 | "value": "Republic of Congo, Uganda, South Africa, Zambia, | 27 | "value": "Republic of Congo, Uganda, South Africa, Zambia, | ||
28 | Egypt, Sudan, Djibouti, Mali, Senegal, Mauritius, Ghana, Africa, | 28 | Egypt, Sudan, Djibouti, Mali, Senegal, Mauritius, Ghana, Africa, | ||
29 | C\u00f4te d'Ivoire, Togo, Democratic Republic of the Congo, Kenya, | 29 | C\u00f4te d'Ivoire, Togo, Democratic Republic of the Congo, Kenya, | ||
30 | Niger, Ethiopia, Nigeria, Malawi" | 30 | Niger, Ethiopia, Nigeria, Malawi" | ||
31 | }, | 31 | }, | ||
32 | { | 32 | { | ||
33 | "key": "GEMET - INSPIRE themes, version 1.0", | 33 | "key": "GEMET - INSPIRE themes, version 1.0", | ||
34 | "value": "Environmental monitoring facilities" | 34 | "value": "Environmental monitoring facilities" | ||
35 | } | 35 | } | ||
36 | ], | 36 | ], | ||
37 | "groups": [], | 37 | "groups": [], | ||
38 | "id": "68002f72-9a08-4faf-b0d1-dacd45e7429d", | 38 | "id": "68002f72-9a08-4faf-b0d1-dacd45e7429d", | ||
39 | "isopen": false, | 39 | "isopen": false, | ||
40 | "license_id": "", | 40 | "license_id": "", | ||
41 | "license_title": "", | 41 | "license_title": "", | ||
42 | "maintainer": "Jana Boruvkova, Custodian,Point of contact", | 42 | "maintainer": "Jana Boruvkova, Custodian,Point of contact", | ||
43 | "maintainer_email": "jana.boruvkova@recetox.muni.cz", | 43 | "maintainer_email": "jana.boruvkova@recetox.muni.cz", | ||
44 | "metadata_created": "2022-10-05T16:23:55.269414", | 44 | "metadata_created": "2022-10-05T16:23:55.269414", | ||
n | 45 | "metadata_modified": "2022-10-05T16:25:31.803212", | n | 45 | "metadata_modified": "2022-10-05T16:26:43.624861", |
46 | "name": "gmp2-africa-region", | 46 | "name": "gmp2-africa-region", | ||
47 | "notes": "GMP2 Africa Region dataset contains information on POPs | 47 | "notes": "GMP2 Africa Region dataset contains information on POPs | ||
48 | concentrations in ambient air, human tissue - breast milk and surface | 48 | concentrations in ambient air, human tissue - breast milk and surface | ||
49 | water; for water-soluble fluorinated POPs only (perfluorooctane | 49 | water; for water-soluble fluorinated POPs only (perfluorooctane | ||
50 | sulfonic acid, its salts and perfluorooctane sulfonyl | 50 | sulfonic acid, its salts and perfluorooctane sulfonyl | ||
51 | fluoride).\r\n\r\nThe second global data collection that can be seen | 51 | fluoride).\r\n\r\nThe second global data collection that can be seen | ||
52 | in this dataset was held during 2013\u20132014 and it contained | 52 | in this dataset was held during 2013\u20132014 and it contained | ||
53 | information on 23 POPs listed in the Stockholm Convention when the | 53 | information on 23 POPs listed in the Stockholm Convention when the | ||
54 | second global data collection took place. The data were sampled | 54 | second global data collection took place. The data were sampled | ||
55 | between 2008 and 2014, however also older data were | 55 | between 2008 and 2014, however also older data were | ||
56 | reported.\r\n\r\nThe Africa Region is characterized by six different | 56 | reported.\r\n\r\nThe Africa Region is characterized by six different | ||
57 | climatic zones that have influence on the movement and distribution of | 57 | climatic zones that have influence on the movement and distribution of | ||
58 | POPs. In addition, except for large deserts in Northern and Southern | 58 | POPs. In addition, except for large deserts in Northern and Southern | ||
59 | Africa, the regions face challenges associated with hot and humid | 59 | Africa, the regions face challenges associated with hot and humid | ||
60 | climatic conditions that promote growth of a myriad of pests and | 60 | climatic conditions that promote growth of a myriad of pests and | ||
61 | disease vectors. POPs have therefore been used in many sectors | 61 | disease vectors. POPs have therefore been used in many sectors | ||
62 | including agriculture, industry and public health to control pests and | 62 | including agriculture, industry and public health to control pests and | ||
63 | diseases.\r\n\r\nThe region collaborated with the following programmes | 63 | diseases.\r\n\r\nThe region collaborated with the following programmes | ||
64 | and strategic partners to obtain data on core media:\r\n\u2022 the | 64 | and strategic partners to obtain data on core media:\r\n\u2022 the | ||
65 | MONET-Africa project coordinated by the Centre of Excellence in | 65 | MONET-Africa project coordinated by the Centre of Excellence in | ||
66 | Environmental Chemistry and Ecotoxicology, Brno, Czech Republic | 66 | Environmental Chemistry and Ecotoxicology, Brno, Czech Republic | ||
67 | (RECETOX),\r\n\u2022 the Global Atmospheric Passive Sampling (GAPS) | 67 | (RECETOX),\r\n\u2022 the Global Atmospheric Passive Sampling (GAPS) | ||
68 | programme coordinated by Environment Canada,\r\n\u2022 the World | 68 | programme coordinated by Environment Canada,\r\n\u2022 the World | ||
69 | Health Organization (WHO) \u2013 Milk survey\r\n\r\nThe POPs Global | 69 | Health Organization (WHO) \u2013 Milk survey\r\n\r\nThe POPs Global | ||
70 | Monitoring Plan Data Warehouse (GMP DWH) has been developed by the | 70 | Monitoring Plan Data Warehouse (GMP DWH) has been developed by the | ||
71 | Stockholm Convention Regional Centre in the Czech Republic through the | 71 | Stockholm Convention Regional Centre in the Czech Republic through the | ||
72 | Research Centre for Toxic Compounds in the Environment, Brno, Czech | 72 | Research Centre for Toxic Compounds in the Environment, Brno, Czech | ||
73 | Republic (RECETOX) and the Institute of Biostatistics and Analyses, | 73 | Republic (RECETOX) and the Institute of Biostatistics and Analyses, | ||
74 | Masaryk University, Brno, Czech Republic, under the guidance of the | 74 | Masaryk University, Brno, Czech Republic, under the guidance of the | ||
75 | GMP Global Coordination Group, and based on Chapter 6 of the Guidance | 75 | GMP Global Coordination Group, and based on Chapter 6 of the Guidance | ||
76 | on the Global Monitoring Plan for Persistent Organic Pollutants | 76 | on the Global Monitoring Plan for Persistent Organic Pollutants | ||
77 | relevant to data handling (UNEP/POPS/COP.6/INF/31).\r\nThe GMP Data | 77 | relevant to data handling (UNEP/POPS/COP.6/INF/31).\r\nThe GMP Data | ||
78 | Warehouse (DWH) is designed to work with data from a wide range of | 78 | Warehouse (DWH) is designed to work with data from a wide range of | ||
79 | heterogeneous sources, such as national monitoring programmes or large | 79 | heterogeneous sources, such as national monitoring programmes or large | ||
80 | international monitoring networks.\r\n\r\nThe data reporting model | 80 | international monitoring networks.\r\n\r\nThe data reporting model | ||
81 | involves compiling and archiving primary GMP data within a | 81 | involves compiling and archiving primary GMP data within a | ||
82 | \u201cregional data repository\u201d in the GMP DWH. In addition, the | 82 | \u201cregional data repository\u201d in the GMP DWH. In addition, the | ||
83 | GMP DWH compiles and archives aggregated data, including supplementary | 83 | GMP DWH compiles and archives aggregated data, including supplementary | ||
84 | data, in cases where no primary data is made available.\r\n\r\nOnly | 84 | data, in cases where no primary data is made available.\r\n\r\nOnly | ||
85 | reliably reported concentration values can be accepted for any spatial | 85 | reliably reported concentration values can be accepted for any spatial | ||
86 | or temporal comparison. Therefore, a multilevel evaluation procedure | 86 | or temporal comparison. Therefore, a multilevel evaluation procedure | ||
87 | based on the annually aggregated concentration values is proposed in | 87 | based on the annually aggregated concentration values is proposed in | ||
88 | order to maintain a high predictive value of the GMP records while | 88 | order to maintain a high predictive value of the GMP records while | ||
89 | avoiding bias in the concentration values.\r\nCompatible data records | 89 | avoiding bias in the concentration values.\r\nCompatible data records | ||
90 | stored in the GMP DWH are considered by members of the respective | 90 | stored in the GMP DWH are considered by members of the respective | ||
91 | regional organization group and validated for further use in the | 91 | regional organization group and validated for further use in the | ||
92 | publication.\r\n", | 92 | publication.\r\n", | ||
n | 93 | "num_resources": 1, | n | 93 | "num_resources": 2, |
94 | "num_tags": 3, | 94 | "num_tags": 3, | ||
95 | "organization": { | 95 | "organization": { | ||
96 | "approval_status": "approved", | 96 | "approval_status": "approved", | ||
97 | "created": "2022-10-05T15:55:42.861710", | 97 | "created": "2022-10-05T15:55:42.861710", | ||
98 | "description": "GMP Data Warehouse provides on-line software tools | 98 | "description": "GMP Data Warehouse provides on-line software tools | ||
99 | supporting the implementation of the Stockholm Convention on | 99 | supporting the implementation of the Stockholm Convention on | ||
100 | Persistent Organic Pollutants, especially the effectiveness evaluation | 100 | Persistent Organic Pollutants, especially the effectiveness evaluation | ||
101 | by providing comparable, harmonised and reliable information on | 101 | by providing comparable, harmonised and reliable information on | ||
102 | persistent organic pollutants levels globally in core environmental | 102 | persistent organic pollutants levels globally in core environmental | ||
103 | matrices: air, human tissues (breast milk, blood), and water.", | 103 | matrices: air, human tissues (breast milk, blood), and water.", | ||
104 | "id": "33d38ce5-45db-4f08-9a3a-d24d4c98a6cc", | 104 | "id": "33d38ce5-45db-4f08-9a3a-d24d4c98a6cc", | ||
105 | "image_url": "2022-10-05-155542.842603sc-logo.svg", | 105 | "image_url": "2022-10-05-155542.842603sc-logo.svg", | ||
106 | "is_organization": true, | 106 | "is_organization": true, | ||
107 | "name": "global-monitoring-plan-data-warehouse", | 107 | "name": "global-monitoring-plan-data-warehouse", | ||
108 | "state": "active", | 108 | "state": "active", | ||
109 | "title": "Global Monitoring Plan Data Warehouse", | 109 | "title": "Global Monitoring Plan Data Warehouse", | ||
110 | "type": "organization" | 110 | "type": "organization" | ||
111 | }, | 111 | }, | ||
112 | "owner_org": "33d38ce5-45db-4f08-9a3a-d24d4c98a6cc", | 112 | "owner_org": "33d38ce5-45db-4f08-9a3a-d24d4c98a6cc", | ||
113 | "private": false, | 113 | "private": false, | ||
114 | "relationships_as_object": [], | 114 | "relationships_as_object": [], | ||
115 | "relationships_as_subject": [], | 115 | "relationships_as_subject": [], | ||
116 | "resources": [ | 116 | "resources": [ | ||
117 | { | 117 | { | ||
118 | "cache_last_updated": null, | 118 | "cache_last_updated": null, | ||
119 | "cache_url": null, | 119 | "cache_url": null, | ||
120 | "created": "2022-10-05T16:25:31.825073", | 120 | "created": "2022-10-05T16:25:31.825073", | ||
121 | "description": "The GMP Data Warehouse (GMP DWH) is an online | 121 | "description": "The GMP Data Warehouse (GMP DWH) is an online | ||
122 | tool developed for handling persistent organic pollutants (POPs) | 122 | tool developed for handling persistent organic pollutants (POPs) | ||
123 | monitoring data generated in the frame of the Global Monitoring Plan | 123 | monitoring data generated in the frame of the Global Monitoring Plan | ||
124 | (GMP) under the Stockholm Convention on POPs.", | 124 | (GMP) under the Stockholm Convention on POPs.", | ||
125 | "format": "HTML", | 125 | "format": "HTML", | ||
126 | "hash": "", | 126 | "hash": "", | ||
127 | "id": "a63ccd96-685f-4c01-8af9-57c3d8fca1bc", | 127 | "id": "a63ccd96-685f-4c01-8af9-57c3d8fca1bc", | ||
128 | "last_modified": null, | 128 | "last_modified": null, | ||
129 | "metadata_modified": "2022-10-05T16:25:31.810282", | 129 | "metadata_modified": "2022-10-05T16:25:31.810282", | ||
130 | "mimetype": null, | 130 | "mimetype": null, | ||
131 | "mimetype_inner": null, | 131 | "mimetype_inner": null, | ||
132 | "name": "GMP2 Data Warehouse Africa Region - Data | 132 | "name": "GMP2 Data Warehouse Africa Region - Data | ||
133 | Visualisations", | 133 | Visualisations", | ||
134 | "package_id": "68002f72-9a08-4faf-b0d1-dacd45e7429d", | 134 | "package_id": "68002f72-9a08-4faf-b0d1-dacd45e7429d", | ||
135 | "position": 0, | 135 | "position": 0, | ||
136 | "resource_type": null, | 136 | "resource_type": null, | ||
137 | "size": null, | 137 | "size": null, | ||
138 | "state": "active", | 138 | "state": "active", | ||
139 | "url": | 139 | "url": | ||
140 | mp.org/2014/data-selection/progress/5d29353c3a0e3e1b390279b3b8187d5f", | 140 | mp.org/2014/data-selection/progress/5d29353c3a0e3e1b390279b3b8187d5f", | ||
141 | "url_type": null | 141 | "url_type": null | ||
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143 | { | ||||
144 | "cache_last_updated": null, | ||||
145 | "cache_url": null, | ||||
146 | "created": "2022-10-05T16:26:43.648926", | ||||
147 | "description": "Map representation of GMP2 dataset for Africa | ||||
148 | Region", | ||||
149 | "format": "WFS", | ||||
150 | "hash": "", | ||||
151 | "id": "43ce0c6f-d7ba-48bf-8763-ff8c3b409c0d", | ||||
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156 | "name": "GMP2 Data Warehouse Africa Region - WFS", | ||||
157 | "package_id": "68002f72-9a08-4faf-b0d1-dacd45e7429d", | ||||
158 | "position": 1, | ||||
159 | "resource_type": null, | ||||
160 | "size": null, | ||||
161 | "state": "active", | ||||
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142 | } | 164 | } | ||
143 | ], | 165 | ], | ||
144 | "state": "draft", | 166 | "state": "draft", | ||
145 | "tags": [ | 167 | "tags": [ | ||
146 | { | 168 | { | ||
147 | "display_name": "environment", | 169 | "display_name": "environment", | ||
148 | "id": "8f1e03f5-a8dd-4f04-8626-c53f7fbeb457", | 170 | "id": "8f1e03f5-a8dd-4f04-8626-c53f7fbeb457", | ||
149 | "name": "environment", | 171 | "name": "environment", | ||
150 | "state": "active", | 172 | "state": "active", | ||
151 | "vocabulary_id": null | 173 | "vocabulary_id": null | ||
152 | }, | 174 | }, | ||
153 | { | 175 | { | ||
154 | "display_name": "global monitoring plan", | 176 | "display_name": "global monitoring plan", | ||
155 | "id": "65050f73-03b8-45a9-ad1a-65437f125807", | 177 | "id": "65050f73-03b8-45a9-ad1a-65437f125807", | ||
156 | "name": "global monitoring plan", | 178 | "name": "global monitoring plan", | ||
157 | "state": "active", | 179 | "state": "active", | ||
158 | "vocabulary_id": null | 180 | "vocabulary_id": null | ||
159 | }, | 181 | }, | ||
160 | { | 182 | { | ||
161 | "display_name": "gmp", | 183 | "display_name": "gmp", | ||
162 | "id": "5fb76f87-c5dc-4695-b0e6-719ef23f479c", | 184 | "id": "5fb76f87-c5dc-4695-b0e6-719ef23f479c", | ||
163 | "name": "gmp", | 185 | "name": "gmp", | ||
164 | "state": "active", | 186 | "state": "active", | ||
165 | "vocabulary_id": null | 187 | "vocabulary_id": null | ||
166 | } | 188 | } | ||
167 | ], | 189 | ], | ||
168 | "title": "GMP2: Africa Region", | 190 | "title": "GMP2: Africa Region", | ||
169 | "type": "dataset", | 191 | "type": "dataset", | ||
170 | "url": "", | 192 | "url": "", | ||
171 | "version": "" | 193 | "version": "" | ||
172 | } | 194 | } |