Changes
On December 2, 2024 at 9:49:48 PM UTC, admin:
-
Changed value of field
doi_status
toTrue
in Adult Income Dataset -
Changed value of field
doi_date_published
to2024-12-02
in Adult Income Dataset -
Added resource Original Metadata to Adult Income Dataset
f | 1 | { | f | 1 | { |
2 | "access_rights": "", | 2 | "access_rights": "", | ||
3 | "author": "Richeek Das", | 3 | "author": "Richeek Das", | ||
4 | "author_email": "", | 4 | "author_email": "", | ||
5 | "citation": [ | 5 | "citation": [ | ||
6 | "https://doi.org/10.48550/arXiv.2011.07495", | 6 | "https://doi.org/10.48550/arXiv.2011.07495", | ||
7 | "https://doi.org/10.48550/arXiv.2312.15994", | 7 | "https://doi.org/10.48550/arXiv.2312.15994", | ||
8 | "https://doi.org/10.48550/arXiv.2205.14545" | 8 | "https://doi.org/10.48550/arXiv.2205.14545" | ||
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11 | "defined_in": "https://doi.org/10.48550/arXiv.2203.12131", | 11 | "defined_in": "https://doi.org/10.48550/arXiv.2203.12131", | ||
12 | "doi": "10.57702/vyj98k2l", | 12 | "doi": "10.57702/vyj98k2l", | ||
n | 13 | "doi_date_published": null, | n | 13 | "doi_date_published": "2024-12-02", |
14 | "doi_publisher": "TIB", | 14 | "doi_publisher": "TIB", | ||
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16 | "domain": "https://service.tib.eu/ldmservice", | 16 | "domain": "https://service.tib.eu/ldmservice", | ||
17 | "extra_authors": [ | 17 | "extra_authors": [ | ||
18 | { | 18 | { | ||
19 | "extra_author": "Samuel Dooley", | 19 | "extra_author": "Samuel Dooley", | ||
20 | "orcid": "" | 20 | "orcid": "" | ||
21 | } | 21 | } | ||
22 | ], | 22 | ], | ||
23 | "groups": [ | 23 | "groups": [ | ||
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38 | "title": "Fairness in machine learning" | 38 | "title": "Fairness in machine learning" | ||
39 | }, | 39 | }, | ||
40 | { | 40 | { | ||
41 | "description": "", | 41 | "description": "", | ||
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44 | "image_display_url": "", | 44 | "image_display_url": "", | ||
45 | "name": "income", | 45 | "name": "income", | ||
46 | "title": "Income" | 46 | "title": "Income" | ||
47 | }, | 47 | }, | ||
48 | { | 48 | { | ||
49 | "description": "", | 49 | "description": "", | ||
50 | "display_name": "Income Prediction", | 50 | "display_name": "Income Prediction", | ||
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52 | "image_display_url": "", | 52 | "image_display_url": "", | ||
53 | "name": "income-prediction", | 53 | "name": "income-prediction", | ||
54 | "title": "Income Prediction" | 54 | "title": "Income Prediction" | ||
55 | }, | 55 | }, | ||
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61 | "name": "machine-learning", | 61 | "name": "machine-learning", | ||
62 | "title": "Machine Learning" | 62 | "title": "Machine Learning" | ||
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70 | "title": "Social Applications" | 70 | "title": "Social Applications" | ||
71 | }, | 71 | }, | ||
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73 | "description": "", | 73 | "description": "", | ||
74 | "display_name": "Tabular data", | 74 | "display_name": "Tabular data", | ||
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76 | "image_display_url": "", | 76 | "image_display_url": "", | ||
77 | "name": "tabular-data", | 77 | "name": "tabular-data", | ||
78 | "title": "Tabular data" | 78 | "title": "Tabular data" | ||
79 | } | 79 | } | ||
80 | ], | 80 | ], | ||
81 | "id": "0e5a7d14-264a-4da1-b011-c3cb421fb18e", | 81 | "id": "0e5a7d14-264a-4da1-b011-c3cb421fb18e", | ||
82 | "isopen": false, | 82 | "isopen": false, | ||
83 | "landing_page": | 83 | "landing_page": | ||
84 | "https://archive.ics.uci.edu/ml/datasets/Adult+Income", | 84 | "https://archive.ics.uci.edu/ml/datasets/Adult+Income", | ||
85 | "license_title": null, | 85 | "license_title": null, | ||
86 | "link_orkg": "", | 86 | "link_orkg": "", | ||
87 | "metadata_created": "2024-12-02T21:49:46.549801", | 87 | "metadata_created": "2024-12-02T21:49:46.549801", | ||
n | 88 | "metadata_modified": "2024-12-02T21:49:46.549806", | n | 88 | "metadata_modified": "2024-12-02T21:49:47.102009", |
89 | "name": "adult-income-dataset", | 89 | "name": "adult-income-dataset", | ||
90 | "notes": "Tabular data is widespread throughout a wide array of | 90 | "notes": "Tabular data is widespread throughout a wide array of | ||
91 | real-world applications, spanning medical diagnosis, housing price | 91 | real-world applications, spanning medical diagnosis, housing price | ||
92 | prediction, loan approval, and robotics. Many of the most sensitive | 92 | prediction, loan approval, and robotics. Many of the most sensitive | ||
93 | forms of tabular data in real-world applications involve an element of | 93 | forms of tabular data in real-world applications involve an element of | ||
94 | fairness considerations where these tables, either directly or in | 94 | fairness considerations where these tables, either directly or in | ||
95 | conjunction, contain a set of protected attributes that partition the | 95 | conjunction, contain a set of protected attributes that partition the | ||
96 | dataset into groups where some protected attributes have higher | 96 | dataset into groups where some protected attributes have higher | ||
97 | performance than others.", | 97 | performance than others.", | ||
n | 98 | "num_resources": 0, | n | 98 | "num_resources": 1, |
99 | "num_tags": 14, | 99 | "num_tags": 14, | ||
100 | "organization": { | 100 | "organization": { | ||
101 | "approval_status": "approved", | 101 | "approval_status": "approved", | ||
102 | "created": "2024-11-25T12:11:38.292601", | 102 | "created": "2024-11-25T12:11:38.292601", | ||
103 | "description": "", | 103 | "description": "", | ||
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106 | "is_organization": true, | 106 | "is_organization": true, | ||
107 | "name": "no-organization", | 107 | "name": "no-organization", | ||
108 | "state": "active", | 108 | "state": "active", | ||
109 | "title": "No Organization", | 109 | "title": "No Organization", | ||
110 | "type": "organization" | 110 | "type": "organization" | ||
111 | }, | 111 | }, | ||
112 | "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", | 112 | "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", | ||
113 | "private": false, | 113 | "private": false, | ||
114 | "relationships_as_object": [], | 114 | "relationships_as_object": [], | ||
115 | "relationships_as_subject": [], | 115 | "relationships_as_subject": [], | ||
t | 116 | "resources": [], | t | 116 | "resources": [ |
117 | { | ||||
118 | "cache_last_updated": null, | ||||
119 | "cache_url": null, | ||||
120 | "created": "2024-12-02T22:29:38", | ||||
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135 | "mls:task", | ||||
136 | "datacite:isDescribedBy" | ||||
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138 | "description": "The json representation of the dataset with its | ||||
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140 | "format": "JSON", | ||||
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118 | "state": "active", | 159 | "state": "active", | ||
119 | "tags": [ | 160 | "tags": [ | ||
120 | { | 161 | { | ||
121 | "display_name": "Adult Income", | 162 | "display_name": "Adult Income", | ||
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124 | "state": "active", | 165 | "state": "active", | ||
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147 | }, | 188 | }, | ||
148 | { | 189 | { | ||
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153 | "vocabulary_id": null | 194 | "vocabulary_id": null | ||
154 | }, | 195 | }, | ||
155 | { | 196 | { | ||
156 | "display_name": "Income", | 197 | "display_name": "Income", | ||
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159 | "state": "active", | 200 | "state": "active", | ||
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166 | "state": "active", | 207 | "state": "active", | ||
167 | "vocabulary_id": null | 208 | "vocabulary_id": null | ||
168 | }, | 209 | }, | ||
169 | { | 210 | { | ||
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173 | "state": "active", | 214 | "state": "active", | ||
174 | "vocabulary_id": null | 215 | "vocabulary_id": null | ||
175 | }, | 216 | }, | ||
176 | { | 217 | { | ||
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178 | "id": "0e465753-f37d-405e-ab6f-81ef0024b640", | 219 | "id": "0e465753-f37d-405e-ab6f-81ef0024b640", | ||
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180 | "state": "active", | 221 | "state": "active", | ||
181 | "vocabulary_id": null | 222 | "vocabulary_id": null | ||
182 | }, | 223 | }, | ||
183 | { | 224 | { | ||
184 | "display_name": "adult income", | 225 | "display_name": "adult income", | ||
185 | "id": "da48bb47-7b6a-43c5-be99-618d5edad51c", | 226 | "id": "da48bb47-7b6a-43c5-be99-618d5edad51c", | ||
186 | "name": "adult income", | 227 | "name": "adult income", | ||
187 | "state": "active", | 228 | "state": "active", | ||
188 | "vocabulary_id": null | 229 | "vocabulary_id": null | ||
189 | }, | 230 | }, | ||
190 | { | 231 | { | ||
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194 | "state": "active", | 235 | "state": "active", | ||
195 | "vocabulary_id": null | 236 | "vocabulary_id": null | ||
196 | }, | 237 | }, | ||
197 | { | 238 | { | ||
198 | "display_name": "income", | 239 | "display_name": "income", | ||
199 | "id": "dba37f5e-54b2-4e23-8860-21f1926b7f4c", | 240 | "id": "dba37f5e-54b2-4e23-8860-21f1926b7f4c", | ||
200 | "name": "income", | 241 | "name": "income", | ||
201 | "state": "active", | 242 | "state": "active", | ||
202 | "vocabulary_id": null | 243 | "vocabulary_id": null | ||
203 | }, | 244 | }, | ||
204 | { | 245 | { | ||
205 | "display_name": "machine learning", | 246 | "display_name": "machine learning", | ||
206 | "id": "9e42784b-6ee7-47e8-a69a-28b8c510212b", | 247 | "id": "9e42784b-6ee7-47e8-a69a-28b8c510212b", | ||
207 | "name": "machine learning", | 248 | "name": "machine learning", | ||
208 | "state": "active", | 249 | "state": "active", | ||
209 | "vocabulary_id": null | 250 | "vocabulary_id": null | ||
210 | }, | 251 | }, | ||
211 | { | 252 | { | ||
212 | "display_name": "social applications", | 253 | "display_name": "social applications", | ||
213 | "id": "0d329da2-1d1d-460a-8366-74e30cd3720a", | 254 | "id": "0d329da2-1d1d-460a-8366-74e30cd3720a", | ||
214 | "name": "social applications", | 255 | "name": "social applications", | ||
215 | "state": "active", | 256 | "state": "active", | ||
216 | "vocabulary_id": null | 257 | "vocabulary_id": null | ||
217 | } | 258 | } | ||
218 | ], | 259 | ], | ||
219 | "title": "Adult Income Dataset", | 260 | "title": "Adult Income Dataset", | ||
220 | "type": "dataset", | 261 | "type": "dataset", | ||
221 | "version": "" | 262 | "version": "" | ||
222 | } | 263 | } |