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      "key": "conforms_to",
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      "value": "paolo.nesi@unifi.it"
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      "value": "paolo.nesi@unifi.it"
            
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    {
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    {
            
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      "key": "contact_name",
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      "value": "Paolo Nesi"
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      "value": "Paolo Nesi"
            
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      "key": "frequency",
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      "value": "Trafair"
            
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    {
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    {
            
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      "key": "identifier",
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      "key": "identifier",
            
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      "value": "air_quality_prediction_coverage_date"
            
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    {
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    {
            
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      "key": "is_version_of",
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      "key": "is_version_of",
            
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      "value": ""
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      "value": ""
            
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    },
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    },
            
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    {
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    {
            
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      "key": "issued",
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      "key": "issued",
            
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      "value": ""
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      "value": ""
            
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    {
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    {
            
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      "key": "language",
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      "key": "language",
            
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      "value": "{ENG,ITA}"
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      "value": "{ENG,ITA}"
            
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    {
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      "key": "modified",
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      "key": "modified",
            
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      "value": "09-06-2020"
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      "value": "09-06-2020"
            
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    {
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    {
            
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      "key": "provenance",
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      "key": "provenance",
            
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      "value": "The Predictions are visibile and available in the 
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      "value": "The Predictions are visibile and available in the 
            
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Snap4City platform (https://www.snap4city.org) and are based on the 
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Snap4City platform (https://www.snap4city.org) and are based on the 
            
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GRAL predictive Model."
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GRAL predictive Model."
            
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      "value": ""
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      "value": ""
            
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    },
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    {
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      "key": "sample_query",
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      "key": "sample_query",
            
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      "value": 
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      "value": 
            
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ight=542&srs=EPSG:4326&format=image/gif&time=2019-10-02T06:00:00.000Z"
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ight=542&srs=EPSG:4326&format=image/gif&time=2019-10-02T06:00:00.000Z"
            
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    },
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    {
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    {
            
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      "key": "temporal_coverage",
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      "key": "temporal_coverage",
            
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      "value": "[]"
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      "value": "[]"
            
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    },
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    {
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    {
            
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      "key": "temporal_end",
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      "key": "temporal_end",
            
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      "value": "2020-11-01T00:00:00.000Z"
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      "value": "2020-11-01T00:00:00.000Z"
            
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    {
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    {
            
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      "key": "temporal_start",
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      "key": "temporal_start",
            
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      "value": "2020-25-05T20:00:00.000Z"
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    {
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    {
            
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      "key": "theme",
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      "key": "theme",
            
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      "value": "[{\"subthemes\": [], \"theme\": \"ENVI\"}]"
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      "value": "[{\"subthemes\": [], \"theme\": \"ENVI\"}]"
            
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  "isopen": true,
            
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  "license_id": "cc-by",
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  "license_id": "cc-by",
            
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  "license_title": "Creative Commons Attribution",
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  "license_title": "Creative Commons Attribution",
            
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  "license_url": "http://www.opendefinition.org/licenses/cc-by",
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  "license_url": "http://www.opendefinition.org/licenses/cc-by",
            
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  "maintainer": "",
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  "maintainer": "",
            
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  "maintainer_email": "",
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  "name": "air_quality_prediction_coverage_date",
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  "name": "air_quality_prediction_coverage_date",
            
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  "notes": "The predictions are realised with a definition of 4x4 
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  "notes": "The predictions are realised with a definition of 4x4 
            
122
meters, at both 3 and 6 meters. The data are available in the 
122
meters, at both 3 and 6 meters. The data are available in the 
            
123
Snap4City portal (https://servicemap.snap4city.org) and have been 
123
Snap4City portal (https://servicemap.snap4city.org) and have been 
            
124
derived from the observations obtained through the sensor network and 
124
derived from the observations obtained through the sensor network and 
            
125
forecast models setup under the framework for the European TRAFAIR 
125
forecast models setup under the framework for the European TRAFAIR 
            
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project.",
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project.",
            
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    "approval_status": "approved",
            
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    "created": "2020-05-25T17:11:16.775491",
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    "created": "2020-05-25T17:11:16.775491",
            
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    "description": "Il progetto TRAFAIR: sviluppare servizi innovativi 
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    "description": "Il progetto TRAFAIR: sviluppare servizi innovativi 
            
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combinando dati su qualit\u00e0 dell\u2019aria, condizioni 
133
combinando dati su qualit\u00e0 dell\u2019aria, condizioni 
            
134
meteorologiche e flusso di traffico per generare nuove informazioni 
134
meteorologiche e flusso di traffico per generare nuove informazioni 
            
135
utili ai cittadini e alle entit\u00e0 
135
utili ai cittadini e alle entit\u00e0 
            
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governative.\r\nL\u2019iniziativa, che ha durata biennale (2018-2020) 
136
governative.\r\nL\u2019iniziativa, che ha durata biennale (2018-2020) 
            
137
ed \u00e8 cofinanziato dal programma europeo \u201cConnecting Europe 
137
ed \u00e8 cofinanziato dal programma europeo \u201cConnecting Europe 
            
138
Facility\u201d CEF nell\u2019ambito delle telecomunicazioni, vede come 
138
Facility\u201d CEF nell\u2019ambito delle telecomunicazioni, vede come 
            
139
capofila l\u2019Universit\u00e0 di Modena e Reggio Emilia e come 
139
capofila l\u2019Universit\u00e0 di Modena e Reggio Emilia e come 
            
140
partner l\u2019Universit\u00e0 degli Studi di Firenze, Universidade de 
140
partner l\u2019Universit\u00e0 degli Studi di Firenze, Universidade de 
            
141
Santiago del Compostela (ES), il Comune di Modena, Regione Toscana, 
141
Santiago del Compostela (ES), il Comune di Modena, Regione Toscana, 
            
142
Concello de Santiago del Compostela (ES), Fundacion Publica Gallega 
142
Concello de Santiago del Compostela (ES), Fundacion Publica Gallega 
            
143
Centro Tecnologico de Supercomputacion de Galicia (ES), Universidad de 
143
Centro Tecnologico de Supercomputacion de Galicia (ES), Universidad de 
            
144
Zaragoza (ES), Lepida S.p.a. (IT).\r\nhttp://trafair.eu/",
144
Zaragoza (ES), Lepida S.p.a. (IT).\r\nhttp://trafair.eu/",
            
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      "description": "The predictions for the city of Florence are 
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      "description": "The predictions for the city of Florence are 
            
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realised with a definition of 4x4 meters, at both 3 and 6 meters. The 
186
realised with a definition of 4x4 meters, at both 3 and 6 meters. The 
            
187
data are available in the Snap4City portal 
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data are available in the Snap4City portal 
            
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(https://servicemap.snap4city.org) and have been derived from the 
188
(https://servicemap.snap4city.org) and have been derived from the 
            
189
observations obtained through the sensor network and forecast models 
189
observations obtained through the sensor network and forecast models 
            
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setup under the framework for the European TRAFAIR project.",
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setup under the framework for the European TRAFAIR project.",
            
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      "distribution_format": "GIF",
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      "distribution_format": "GIF",
            
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      "format": "WMS",
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      "format": "WMS",
            
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      "hash": "",
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      "id": "a19ce4bf-6524-483e-a47a-20b9278e13b5",
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      "url": 
            
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city.org/geoserver/Snap4City/wms?service=WMS&request=GetCapabilities",
            
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        "last_success": null,
            
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        "mimetype": null,
            
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        "reason": "No value for ckanext-archiver.cache_url_root in 
            
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config",
            
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        "resource_timestamp": null,
            
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        "size": 0,
            
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        "status": "System error during archival",
            
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        "status_id": 23,
            
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        "updated": "2023-06-23T18:06:03.175147",
            
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        "url_redirected_to": null
            
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      },
            
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      "cache_last_updated": null,
            
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      "cache_url": null,
            
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      "created": "2020-11-02T15:12:44.339380",
            
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      "datastore_active": false,
            
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      "description": "The predictions for the city of Pisa are 
            
238
realised with a definition of 4x4 meters, at both 3 and 6 meters. The 
            
239
data are available in the Snap4City portal 
            
240
(https://servicemap.snap4city.org) and have been derived from the 
            
241
observations obtained through the sensor network and forecast models 
            
242
setup under the framework for the European TRAFAIR project.",
            
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      "distribution_format": "GIF",
            
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      "format": "WMS",
            
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      "hash": "",
            
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      "id": "495111be-c59e-4a87-882a-f848290abfa2",
            
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      "last_modified": "2020-11-02T00:00:00",
            
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      "license_type": 
            
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"https://w3id.org/italia/controlled-vocabulary/licences/A21_CCBY40",
            
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      "mimetype": null,
            
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      "mimetype_inner": null,
            
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      "name": "GRALheatmapPisaLivorno6m",
            
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      "package_id": "e15f48c3-420d-4b02-b203-66c40496476f",
            
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      "position": 1,
            
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      "resource_type": null,
            
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      "size": null,
            
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      "state": "active",
            
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      "url": 
            
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city.org/geoserver/Snap4City/wms?service=WMS&request=GetCapabilities",
            
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      "url_type": null
            
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    }
261
    }
            
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  ],
262
  ],
            
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  "state": "active",
263
  "state": "active",
            
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  "tags": [],
264
  "tags": [],
            
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  "title": "Air Quality Prediction Coverage based on date, heatmaps in 
265
  "title": "Air Quality Prediction Coverage based on date, heatmaps in 
            
214
the cities of Firenze, Pisa and Livorno on NOx.",
266
the cities of Firenze, Pisa and Livorno on NOx.",
            
215
  "type": "dataset",
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  "type": "dataset",
            
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  "url": "https://servicemap.snap4city.org/",
268
  "url": "https://servicemap.snap4city.org/",
            
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  "version": ""
269
  "version": ""
            
218
}
270
}