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En el instante 25 de octubre de 2025, 3:36:22 UTC,
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Añadido recurso Simulación SUMO de Tráfico Vehicular en el Centro de Querétaro a Simulación SUMO de Tráfico Vehicular en el Centro de Querétaro
| f | 1 | { | f | 1 | { |
| 2 | "author": "Alberto Garc\u00eda Robledo <agarcia@centrogeo.edu.mx>", | 2 | "author": "Alberto Garc\u00eda Robledo <agarcia@centrogeo.edu.mx>", | ||
| 3 | "author_email": null, | 3 | "author_email": null, | ||
| 4 | "creator_user_id": "a3da3ec9-3fd4-47a4-8d04-0a90b09614e0", | 4 | "creator_user_id": "a3da3ec9-3fd4-47a4-8d04-0a90b09614e0", | ||
| 5 | "extras": [ | 5 | "extras": [ | ||
| 6 | { | 6 | { | ||
| 7 | "key": "Autores de contenido", | 7 | "key": "Autores de contenido", | ||
| 8 | "value": "Alberto Garc\u00eda Robledo | 8 | "value": "Alberto Garc\u00eda Robledo | ||
| 9 | <agarcia@centrogeo.edu.mx>" | 9 | <agarcia@centrogeo.edu.mx>" | ||
| 10 | }, | 10 | }, | ||
| 11 | { | 11 | { | ||
| 12 | "key": "Autores t\u00e9cnicos", | 12 | "key": "Autores t\u00e9cnicos", | ||
| 13 | "value": "Alberto Garc\u00eda Robledo | 13 | "value": "Alberto Garc\u00eda Robledo | ||
| 14 | <agarcia@centrogeo.edu.mx>" | 14 | <agarcia@centrogeo.edu.mx>" | ||
| 15 | }, | 15 | }, | ||
| 16 | { | 16 | { | ||
| 17 | "key": "Contacto de contenidos", | 17 | "key": "Contacto de contenidos", | ||
| 18 | "value": "Alberto Garc\u00eda Robledo | 18 | "value": "Alberto Garc\u00eda Robledo | ||
| 19 | <agarcia@centrogeo.edu.mx>" | 19 | <agarcia@centrogeo.edu.mx>" | ||
| 20 | }, | 20 | }, | ||
| 21 | { | 21 | { | ||
| 22 | "key": "Contacto t\u00e9cnico", | 22 | "key": "Contacto t\u00e9cnico", | ||
| 23 | "value": "Alberto Garc\u00eda Robledo | 23 | "value": "Alberto Garc\u00eda Robledo | ||
| 24 | <agarcia@centrogeo.edu.mx>" | 24 | <agarcia@centrogeo.edu.mx>" | ||
| 25 | }, | 25 | }, | ||
| 26 | { | 26 | { | ||
| 27 | "key": "Fecha de actualizaci\u00f3n", | 27 | "key": "Fecha de actualizaci\u00f3n", | ||
| 28 | "value": "06/07/22" | 28 | "value": "06/07/22" | ||
| 29 | }, | 29 | }, | ||
| 30 | { | 30 | { | ||
| 31 | "key": "Identificador hash", | 31 | "key": "Identificador hash", | ||
| 32 | "value": "6b3eabdaf30a" | 32 | "value": "6b3eabdaf30a" | ||
| 33 | }, | 33 | }, | ||
| 34 | { | 34 | { | ||
| 35 | "key": "Idioma", | 35 | "key": "Idioma", | ||
| 36 | "value": "Ingl\u00e9s" | 36 | "value": "Ingl\u00e9s" | ||
| 37 | }, | 37 | }, | ||
| 38 | { | 38 | { | ||
| 39 | "key": "Tipo", | 39 | "key": "Tipo", | ||
| 40 | "value": "Visualizaci\u00f3n" | 40 | "value": "Visualizaci\u00f3n" | ||
| 41 | }, | 41 | }, | ||
| 42 | { | 42 | { | ||
| 43 | "key": "URL", | 43 | "key": "URL", | ||
| 44 | "value": | 44 | "value": | ||
| 45 | sualizacion.observatoriogeo.mx/sylvereyesumo/dashboard/sylvereyesumo/" | 45 | sualizacion.observatoriogeo.mx/sylvereyesumo/dashboard/sylvereyesumo/" | ||
| 46 | }, | 46 | }, | ||
| 47 | { | 47 | { | ||
| 48 | "key": "URL del thumbnail", | 48 | "key": "URL del thumbnail", | ||
| 49 | "value": | 49 | "value": | ||
| 50 | vatoriogeo.mx/wp-content/uploads/2025/10/demo-dash-sylvereye-dash.png" | 50 | vatoriogeo.mx/wp-content/uploads/2025/10/demo-dash-sylvereye-dash.png" | ||
| 51 | }, | 51 | }, | ||
| 52 | { | 52 | { | ||
| 53 | "key": "Versi\u00f3n", | 53 | "key": "Versi\u00f3n", | ||
| 54 | "value": "v1.0.0" | 54 | "value": "v1.0.0" | ||
| 55 | } | 55 | } | ||
| 56 | ], | 56 | ], | ||
| 57 | "groups": [ | 57 | "groups": [ | ||
| 58 | { | 58 | { | ||
| 59 | "description": "", | 59 | "description": "", | ||
| 60 | "display_name": "Visualizaciones", | 60 | "display_name": "Visualizaciones", | ||
| 61 | "id": "2b5bec50-1abb-4886-841d-ea9b266fefc8", | 61 | "id": "2b5bec50-1abb-4886-841d-ea9b266fefc8", | ||
| 62 | "image_display_url": "", | 62 | "image_display_url": "", | ||
| 63 | "name": "visualizaciones", | 63 | "name": "visualizaciones", | ||
| 64 | "title": "Visualizaciones" | 64 | "title": "Visualizaciones" | ||
| 65 | } | 65 | } | ||
| 66 | ], | 66 | ], | ||
| 67 | "id": "b4e93120-fe8b-4147-a331-440177402ab7", | 67 | "id": "b4e93120-fe8b-4147-a331-440177402ab7", | ||
| 68 | "isopen": false, | 68 | "isopen": false, | ||
| 69 | "license_id": null, | 69 | "license_id": null, | ||
| 70 | "license_title": null, | 70 | "license_title": null, | ||
| 71 | "maintainer": null, | 71 | "maintainer": null, | ||
| 72 | "maintainer_email": null, | 72 | "maintainer_email": null, | ||
| 73 | "metadata_created": "2025-10-25T03:36:21.672391", | 73 | "metadata_created": "2025-10-25T03:36:21.672391", | ||
| n | 74 | "metadata_modified": "2025-10-25T03:36:21.672405", | n | 74 | "metadata_modified": "2025-10-25T03:36:22.189585", |
| 75 | "name": "6b3eabdaf30a", | 75 | "name": "6b3eabdaf30a", | ||
| 76 | "notes": "El tablero \u201cSimulaci\u00f3n SUMO de Tr\u00e1fico | 76 | "notes": "El tablero \u201cSimulaci\u00f3n SUMO de Tr\u00e1fico | ||
| 77 | Vehicular en el Centro de Quer\u00e9taro\u201d presenta una | 77 | Vehicular en el Centro de Quer\u00e9taro\u201d presenta una | ||
| 78 | visualizaci\u00f3n interactiva desarrollada con el framework Dash, la | 78 | visualizaci\u00f3n interactiva desarrollada con el framework Dash, la | ||
| 79 | cual utiliza la biblioteca Dash Sylvereye para el an\u00e1lisis | 79 | cual utiliza la biblioteca Dash Sylvereye para el an\u00e1lisis | ||
| 80 | postmortem de una simulaci\u00f3n vehicular realizada sobre la red de | 80 | postmortem de una simulaci\u00f3n vehicular realizada sobre la red de | ||
| 81 | calles del centro de la ciudad de Quer\u00e9taro, M\u00e9xico.\n\nLas | 81 | calles del centro de la ciudad de Quer\u00e9taro, M\u00e9xico.\n\nLas | ||
| 82 | simulaciones fueron generadas con SUMO (Simulation of Urban MObility), | 82 | simulaciones fueron generadas con SUMO (Simulation of Urban MObility), | ||
| 83 | un simulador ampliamente usado en el an\u00e1lisis urbano y de | 83 | un simulador ampliamente usado en el an\u00e1lisis urbano y de | ||
| 84 | transporte, que permite modelar el movimiento de veh\u00edculos a lo | 84 | transporte, que permite modelar el movimiento de veh\u00edculos a lo | ||
| 85 | largo del tiempo en redes urbanas reales.\n\nEn el dashboard, la | 85 | largo del tiempo en redes urbanas reales.\n\nEn el dashboard, la | ||
| 86 | visualizaci\u00f3n principal muestra la red vial de Quer\u00e9taro | 86 | visualizaci\u00f3n principal muestra la red vial de Quer\u00e9taro | ||
| 87 | sobre un mapa interactivo, en la cual los usuarios pueden:\n\n* | 87 | sobre un mapa interactivo, en la cual los usuarios pueden:\n\n* | ||
| 88 | Activar o desactivar capas visuales mediante una lista de | 88 | Activar o desactivar capas visuales mediante una lista de | ||
| 89 | selecci\u00f3n.\n* Mostrar marcadores en los tramos con mayor flujo | 89 | selecci\u00f3n.\n* Mostrar marcadores en los tramos con mayor flujo | ||
| 90 | vehicular o en los veh\u00edculos m\u00e1s lentos, seg\u00fan la | 90 | vehicular o en los veh\u00edculos m\u00e1s lentos, seg\u00fan la | ||
| 91 | opci\u00f3n elegida.\n* Ajustar atributos visuales de los tramos (como | 91 | opci\u00f3n elegida.\n* Ajustar atributos visuales de los tramos (como | ||
| 92 | la transparencia y el ancho de las l\u00edneas) en funci\u00f3n del | 92 | la transparencia y el ancho de las l\u00edneas) en funci\u00f3n del | ||
| 93 | n\u00famero de veh\u00edculos, para resaltar las zonas con mayor | 93 | n\u00famero de veh\u00edculos, para resaltar las zonas con mayor | ||
| 94 | congesti\u00f3n.\n* Utilizar un control deslizante temporal para | 94 | congesti\u00f3n.\n* Utilizar un control deslizante temporal para | ||
| 95 | seleccionar y visualizar el estado del tr\u00e1fico en un instante | 95 | seleccionar y visualizar el estado del tr\u00e1fico en un instante | ||
| 96 | espec\u00edfico de la simulaci\u00f3n.\n\nEsta combinaci\u00f3n de | 96 | espec\u00edfico de la simulaci\u00f3n.\n\nEsta combinaci\u00f3n de | ||
| 97 | controles permite analizar din\u00e1micamente el comportamiento del | 97 | controles permite analizar din\u00e1micamente el comportamiento del | ||
| 98 | tr\u00e1fico, identificar cuellos de botella y visualizar su | 98 | tr\u00e1fico, identificar cuellos de botella y visualizar su | ||
| 99 | evoluci\u00f3n temporal.\n\nEl tablero demuestra las capacidades de | 99 | evoluci\u00f3n temporal.\n\nEl tablero demuestra las capacidades de | ||
| 100 | Dash Sylvereye, una biblioteca creada en el Observatorio Metropolitano | 100 | Dash Sylvereye, una biblioteca creada en el Observatorio Metropolitano | ||
| 101 | CentroGeo, capaz de renderizar redes viales a escala urbana con | 101 | CentroGeo, capaz de renderizar redes viales a escala urbana con | ||
| 102 | aceleraci\u00f3n WebGL, y de integrarse de forma nativa con | 102 | aceleraci\u00f3n WebGL, y de integrarse de forma nativa con | ||
| 103 | componentes interactivos de Dash para construir dashboards | 103 | componentes interactivos de Dash para construir dashboards | ||
| 104 | anal\u00edticos completamente en Python.\n\nEn conjunto, la | 104 | anal\u00edticos completamente en Python.\n\nEn conjunto, la | ||
| 105 | simulaci\u00f3n ofrece una herramienta poderosa para el an\u00e1lisis | 105 | simulaci\u00f3n ofrece una herramienta poderosa para el an\u00e1lisis | ||
| 106 | visual de la movilidad urbana, permitiendo explorar patrones de | 106 | visual de la movilidad urbana, permitiendo explorar patrones de | ||
| 107 | tr\u00e1fico y su din\u00e1mica temporal con un enfoque reproducible y | 107 | tr\u00e1fico y su din\u00e1mica temporal con un enfoque reproducible y | ||
| 108 | extensible a otras ciudades.", | 108 | extensible a otras ciudades.", | ||
| n | 109 | "num_resources": 0, | n | 109 | "num_resources": 1, |
| 110 | "num_tags": 26, | 110 | "num_tags": 26, | ||
| 111 | "organization": { | 111 | "organization": { | ||
| 112 | "approval_status": "approved", | 112 | "approval_status": "approved", | ||
| 113 | "created": "2022-05-19T00:10:30.480393", | 113 | "created": "2022-05-19T00:10:30.480393", | ||
| 114 | "description": "Observatorio Metropolitano CentroGeo", | 114 | "description": "Observatorio Metropolitano CentroGeo", | ||
| 115 | "id": "b3b3a79d-748a-4464-9471-732b6c74ec53", | 115 | "id": "b3b3a79d-748a-4464-9471-732b6c74ec53", | ||
| 116 | "image_url": | 116 | "image_url": | ||
| 117 | "2022-05-19-001030.456616FullColor1280x1024LogoOnly.png", | 117 | "2022-05-19-001030.456616FullColor1280x1024LogoOnly.png", | ||
| 118 | "is_organization": true, | 118 | "is_organization": true, | ||
| 119 | "name": "observatorio-metropolitano-centrogeo", | 119 | "name": "observatorio-metropolitano-centrogeo", | ||
| 120 | "state": "active", | 120 | "state": "active", | ||
| 121 | "title": "Observatorio Metropolitano CentroGeo", | 121 | "title": "Observatorio Metropolitano CentroGeo", | ||
| 122 | "type": "organization" | 122 | "type": "organization" | ||
| 123 | }, | 123 | }, | ||
| 124 | "owner_org": "b3b3a79d-748a-4464-9471-732b6c74ec53", | 124 | "owner_org": "b3b3a79d-748a-4464-9471-732b6c74ec53", | ||
| 125 | "private": false, | 125 | "private": false, | ||
| 126 | "relationships_as_object": [], | 126 | "relationships_as_object": [], | ||
| 127 | "relationships_as_subject": [], | 127 | "relationships_as_subject": [], | ||
| t | 128 | "resources": [], | t | 128 | "resources": [ |
| 129 | { | ||||
| 130 | "cache_last_updated": null, | ||||
| 131 | "cache_url": null, | ||||
| 132 | "created": "2025-10-25T03:36:22.267752", | ||||
| 133 | "datastore_active": false, | ||||
| 134 | "description": "El tablero \u201cSimulaci\u00f3n SUMO de | ||||
| 135 | Tr\u00e1fico Vehicular en el Centro de Quer\u00e9taro\u201d presenta | ||||
| 136 | una visualizaci\u00f3n interactiva desarrollada con el framework Dash, | ||||
| 137 | la cual utiliza la biblioteca Dash Sylvereye para el an\u00e1lisis | ||||
| 138 | postmortem de una simulaci\u00f3n vehicular realizada sobre la red de | ||||
| 139 | calles del centro de la ciudad de Quer\u00e9taro, M\u00e9xico.\n\nLas | ||||
| 140 | simulaciones fueron generadas con SUMO (Simulation of Urban MObility), | ||||
| 141 | un simulador ampliamente usado en el an\u00e1lisis urbano y de | ||||
| 142 | transporte, que permite modelar el movimiento de veh\u00edculos a lo | ||||
| 143 | largo del tiempo en redes urbanas reales.\n\nEn el dashboard, la | ||||
| 144 | visualizaci\u00f3n principal muestra la red vial de Quer\u00e9taro | ||||
| 145 | sobre un mapa interactivo, en la cual los usuarios pueden:\n\n* | ||||
| 146 | Activar o desactivar capas visuales mediante una lista de | ||||
| 147 | selecci\u00f3n.\n* Mostrar marcadores en los tramos con mayor flujo | ||||
| 148 | vehicular o en los veh\u00edculos m\u00e1s lentos, seg\u00fan la | ||||
| 149 | opci\u00f3n elegida.\n* Ajustar atributos visuales de los tramos (como | ||||
| 150 | la transparencia y el ancho de las l\u00edneas) en funci\u00f3n del | ||||
| 151 | n\u00famero de veh\u00edculos, para resaltar las zonas con mayor | ||||
| 152 | congesti\u00f3n.\n* Utilizar un control deslizante temporal para | ||||
| 153 | seleccionar y visualizar el estado del tr\u00e1fico en un instante | ||||
| 154 | espec\u00edfico de la simulaci\u00f3n.\n\nEsta combinaci\u00f3n de | ||||
| 155 | controles permite analizar din\u00e1micamente el comportamiento del | ||||
| 156 | tr\u00e1fico, identificar cuellos de botella y visualizar su | ||||
| 157 | evoluci\u00f3n temporal.\n\nEl tablero demuestra las capacidades de | ||||
| 158 | Dash Sylvereye, una biblioteca creada en el Observatorio Metropolitano | ||||
| 159 | CentroGeo, capaz de renderizar redes viales a escala urbana con | ||||
| 160 | aceleraci\u00f3n WebGL, y de integrarse de forma nativa con | ||||
| 161 | componentes interactivos de Dash para construir dashboards | ||||
| 162 | anal\u00edticos completamente en Python.\n\nEn conjunto, la | ||||
| 163 | simulaci\u00f3n ofrece una herramienta poderosa para el an\u00e1lisis | ||||
| 164 | visual de la movilidad urbana, permitiendo explorar patrones de | ||||
| 165 | tr\u00e1fico y su din\u00e1mica temporal con un enfoque reproducible y | ||||
| 166 | extensible a otras ciudades.", | ||||
| 167 | "format": "HTML", | ||||
| 168 | "hash": "", | ||||
| 169 | "id": "9e1ccaa6-34d6-40ed-b25f-4cff5840146e", | ||||
| 170 | "last_modified": null, | ||||
| 171 | "metadata_modified": "2025-10-25T03:36:22.195277", | ||||
| 172 | "mimetype": null, | ||||
| 173 | "mimetype_inner": null, | ||||
| 174 | "name": "Simulaci\u00f3n SUMO de Tr\u00e1fico Vehicular en el | ||||
| 175 | Centro de Quer\u00e9taro", | ||||
| 176 | "package_id": "b4e93120-fe8b-4147-a331-440177402ab7", | ||||
| 177 | "position": 0, | ||||
| 178 | "resource_type": null, | ||||
| 179 | "size": null, | ||||
| 180 | "state": "active", | ||||
| 181 | "url": | ||||
| 182 | ualizacion.observatoriogeo.mx/sylvereyesumo/dashboard/sylvereyesumo/", | ||||
| 183 | "url_type": null | ||||
| 184 | } | ||||
| 185 | ], | ||||
| 129 | "state": "active", | 186 | "state": "active", | ||
| 130 | "tags": [ | 187 | "tags": [ | ||
| 131 | { | 188 | { | ||
| 132 | "display_name": "albertogarob", | 189 | "display_name": "albertogarob", | ||
| 133 | "id": "b079b3e9-8dbb-4423-88fb-f095153d314a", | 190 | "id": "b079b3e9-8dbb-4423-88fb-f095153d314a", | ||
| 134 | "name": "albertogarob", | 191 | "name": "albertogarob", | ||
| 135 | "state": "active", | 192 | "state": "active", | ||
| 136 | "vocabulary_id": null | 193 | "vocabulary_id": null | ||
| 137 | }, | 194 | }, | ||
| 138 | { | 195 | { | ||
| 139 | "display_name": "analisis-de-movilidad", | 196 | "display_name": "analisis-de-movilidad", | ||
| 140 | "id": "b277d691-952a-4fe9-952a-a53c0ef92e39", | 197 | "id": "b277d691-952a-4fe9-952a-a53c0ef92e39", | ||
| 141 | "name": "analisis-de-movilidad", | 198 | "name": "analisis-de-movilidad", | ||
| 142 | "state": "active", | 199 | "state": "active", | ||
| 143 | "vocabulary_id": null | 200 | "vocabulary_id": null | ||
| 144 | }, | 201 | }, | ||
| 145 | { | 202 | { | ||
| 146 | "display_name": "analisis-postmortem", | 203 | "display_name": "analisis-postmortem", | ||
| 147 | "id": "e758a315-ad22-4784-9a76-06a86613bfac", | 204 | "id": "e758a315-ad22-4784-9a76-06a86613bfac", | ||
| 148 | "name": "analisis-postmortem", | 205 | "name": "analisis-postmortem", | ||
| 149 | "state": "active", | 206 | "state": "active", | ||
| 150 | "vocabulary_id": null | 207 | "vocabulary_id": null | ||
| 151 | }, | 208 | }, | ||
| 152 | { | 209 | { | ||
| 153 | "display_name": "analisis-temporal", | 210 | "display_name": "analisis-temporal", | ||
| 154 | "id": "e6500def-d7fc-467d-a002-ad0447691c57", | 211 | "id": "e6500def-d7fc-467d-a002-ad0447691c57", | ||
| 155 | "name": "analisis-temporal", | 212 | "name": "analisis-temporal", | ||
| 156 | "state": "active", | 213 | "state": "active", | ||
| 157 | "vocabulary_id": null | 214 | "vocabulary_id": null | ||
| 158 | }, | 215 | }, | ||
| 159 | { | 216 | { | ||
| 160 | "display_name": "centrogeo", | 217 | "display_name": "centrogeo", | ||
| 161 | "id": "1f0e8926-452a-4e96-8723-2161d56eaddd", | 218 | "id": "1f0e8926-452a-4e96-8723-2161d56eaddd", | ||
| 162 | "name": "centrogeo", | 219 | "name": "centrogeo", | ||
| 163 | "state": "active", | 220 | "state": "active", | ||
| 164 | "vocabulary_id": null | 221 | "vocabulary_id": null | ||
| 165 | }, | 222 | }, | ||
| 166 | { | 223 | { | ||
| 167 | "display_name": "congestion-vial", | 224 | "display_name": "congestion-vial", | ||
| 168 | "id": "5aebed54-3a9c-4a70-a31b-6f85ab79211d", | 225 | "id": "5aebed54-3a9c-4a70-a31b-6f85ab79211d", | ||
| 169 | "name": "congestion-vial", | 226 | "name": "congestion-vial", | ||
| 170 | "state": "active", | 227 | "state": "active", | ||
| 171 | "vocabulary_id": null | 228 | "vocabulary_id": null | ||
| 172 | }, | 229 | }, | ||
| 173 | { | 230 | { | ||
| 174 | "display_name": "cuellos-de-botella", | 231 | "display_name": "cuellos-de-botella", | ||
| 175 | "id": "d77000fe-87e8-4daa-98ad-953b5d4f1d70", | 232 | "id": "d77000fe-87e8-4daa-98ad-953b5d4f1d70", | ||
| 176 | "name": "cuellos-de-botella", | 233 | "name": "cuellos-de-botella", | ||
| 177 | "state": "active", | 234 | "state": "active", | ||
| 178 | "vocabulary_id": null | 235 | "vocabulary_id": null | ||
| 179 | }, | 236 | }, | ||
| 180 | { | 237 | { | ||
| 181 | "display_name": "dash", | 238 | "display_name": "dash", | ||
| 182 | "id": "e41e669d-e3a1-4afc-9363-fb80dce5ae26", | 239 | "id": "e41e669d-e3a1-4afc-9363-fb80dce5ae26", | ||
| 183 | "name": "dash", | 240 | "name": "dash", | ||
| 184 | "state": "active", | 241 | "state": "active", | ||
| 185 | "vocabulary_id": null | 242 | "vocabulary_id": null | ||
| 186 | }, | 243 | }, | ||
| 187 | { | 244 | { | ||
| 188 | "display_name": "dash-sylvereye", | 245 | "display_name": "dash-sylvereye", | ||
| 189 | "id": "bfc898f3-102d-4857-9f1a-4d55d708beca", | 246 | "id": "bfc898f3-102d-4857-9f1a-4d55d708beca", | ||
| 190 | "name": "dash-sylvereye", | 247 | "name": "dash-sylvereye", | ||
| 191 | "state": "active", | 248 | "state": "active", | ||
| 192 | "vocabulary_id": null | 249 | "vocabulary_id": null | ||
| 193 | }, | 250 | }, | ||
| 194 | { | 251 | { | ||
| 195 | "display_name": "datos-urbanos", | 252 | "display_name": "datos-urbanos", | ||
| 196 | "id": "c1156a9b-59a8-49c2-a7e8-79f46dfe2642", | 253 | "id": "c1156a9b-59a8-49c2-a7e8-79f46dfe2642", | ||
| 197 | "name": "datos-urbanos", | 254 | "name": "datos-urbanos", | ||
| 198 | "state": "active", | 255 | "state": "active", | ||
| 199 | "vocabulary_id": null | 256 | "vocabulary_id": null | ||
| 200 | }, | 257 | }, | ||
| 201 | { | 258 | { | ||
| 202 | "display_name": "frameworks-de-visualizacion", | 259 | "display_name": "frameworks-de-visualizacion", | ||
| 203 | "id": "c98bd401-5049-4272-9b85-4cf7b45bdd33", | 260 | "id": "c98bd401-5049-4272-9b85-4cf7b45bdd33", | ||
| 204 | "name": "frameworks-de-visualizacion", | 261 | "name": "frameworks-de-visualizacion", | ||
| 205 | "state": "active", | 262 | "state": "active", | ||
| 206 | "vocabulary_id": null | 263 | "vocabulary_id": null | ||
| 207 | }, | 264 | }, | ||
| 208 | { | 265 | { | ||
| 209 | "display_name": "movilidad-urbana", | 266 | "display_name": "movilidad-urbana", | ||
| 210 | "id": "3587f36b-4788-4a7e-bc95-2f8148421454", | 267 | "id": "3587f36b-4788-4a7e-bc95-2f8148421454", | ||
| 211 | "name": "movilidad-urbana", | 268 | "name": "movilidad-urbana", | ||
| 212 | "state": "active", | 269 | "state": "active", | ||
| 213 | "vocabulary_id": null | 270 | "vocabulary_id": null | ||
| 214 | }, | 271 | }, | ||
| 215 | { | 272 | { | ||
| 216 | "display_name": "observatorio-metropolitano", | 273 | "display_name": "observatorio-metropolitano", | ||
| 217 | "id": "c3a142dd-ecb6-4698-b5a1-01913558a524", | 274 | "id": "c3a142dd-ecb6-4698-b5a1-01913558a524", | ||
| 218 | "name": "observatorio-metropolitano", | 275 | "name": "observatorio-metropolitano", | ||
| 219 | "state": "active", | 276 | "state": "active", | ||
| 220 | "vocabulary_id": null | 277 | "vocabulary_id": null | ||
| 221 | }, | 278 | }, | ||
| 222 | { | 279 | { | ||
| 223 | "display_name": "python", | 280 | "display_name": "python", | ||
| 224 | "id": "ea0c471b-9b13-4dd3-8381-aed24f2f855c", | 281 | "id": "ea0c471b-9b13-4dd3-8381-aed24f2f855c", | ||
| 225 | "name": "python", | 282 | "name": "python", | ||
| 226 | "state": "active", | 283 | "state": "active", | ||
| 227 | "vocabulary_id": null | 284 | "vocabulary_id": null | ||
| 228 | }, | 285 | }, | ||
| 229 | { | 286 | { | ||
| 230 | "display_name": "queretaro", | 287 | "display_name": "queretaro", | ||
| 231 | "id": "8b0a7865-6ede-462a-a978-a766fa428786", | 288 | "id": "8b0a7865-6ede-462a-a978-a766fa428786", | ||
| 232 | "name": "queretaro", | 289 | "name": "queretaro", | ||
| 233 | "state": "active", | 290 | "state": "active", | ||
| 234 | "vocabulary_id": null | 291 | "vocabulary_id": null | ||
| 235 | }, | 292 | }, | ||
| 236 | { | 293 | { | ||
| 237 | "display_name": "red-vial", | 294 | "display_name": "red-vial", | ||
| 238 | "id": "cb6f596d-cb1a-46d6-9f8b-b0904a3352cc", | 295 | "id": "cb6f596d-cb1a-46d6-9f8b-b0904a3352cc", | ||
| 239 | "name": "red-vial", | 296 | "name": "red-vial", | ||
| 240 | "state": "active", | 297 | "state": "active", | ||
| 241 | "vocabulary_id": null | 298 | "vocabulary_id": null | ||
| 242 | }, | 299 | }, | ||
| 243 | { | 300 | { | ||
| 244 | "display_name": "redes-de-calles", | 301 | "display_name": "redes-de-calles", | ||
| 245 | "id": "ec3fa987-5efd-4f4d-a2ee-ca193d274eed", | 302 | "id": "ec3fa987-5efd-4f4d-a2ee-ca193d274eed", | ||
| 246 | "name": "redes-de-calles", | 303 | "name": "redes-de-calles", | ||
| 247 | "state": "active", | 304 | "state": "active", | ||
| 248 | "vocabulary_id": null | 305 | "vocabulary_id": null | ||
| 249 | }, | 306 | }, | ||
| 250 | { | 307 | { | ||
| 251 | "display_name": "simulacion-computacional", | 308 | "display_name": "simulacion-computacional", | ||
| 252 | "id": "80b2002e-6d88-4e28-8061-d28e55a67f54", | 309 | "id": "80b2002e-6d88-4e28-8061-d28e55a67f54", | ||
| 253 | "name": "simulacion-computacional", | 310 | "name": "simulacion-computacional", | ||
| 254 | "state": "active", | 311 | "state": "active", | ||
| 255 | "vocabulary_id": null | 312 | "vocabulary_id": null | ||
| 256 | }, | 313 | }, | ||
| 257 | { | 314 | { | ||
| 258 | "display_name": "simulacion-de-trafico", | 315 | "display_name": "simulacion-de-trafico", | ||
| 259 | "id": "7a39f84d-7f97-4c22-abf3-a3fee6a641bb", | 316 | "id": "7a39f84d-7f97-4c22-abf3-a3fee6a641bb", | ||
| 260 | "name": "simulacion-de-trafico", | 317 | "name": "simulacion-de-trafico", | ||
| 261 | "state": "active", | 318 | "state": "active", | ||
| 262 | "vocabulary_id": null | 319 | "vocabulary_id": null | ||
| 263 | }, | 320 | }, | ||
| 264 | { | 321 | { | ||
| 265 | "display_name": "simulacion-urbana", | 322 | "display_name": "simulacion-urbana", | ||
| 266 | "id": "995852e8-c993-429c-bdda-31dd13d18747", | 323 | "id": "995852e8-c993-429c-bdda-31dd13d18747", | ||
| 267 | "name": "simulacion-urbana", | 324 | "name": "simulacion-urbana", | ||
| 268 | "state": "active", | 325 | "state": "active", | ||
| 269 | "vocabulary_id": null | 326 | "vocabulary_id": null | ||
| 270 | }, | 327 | }, | ||
| 271 | { | 328 | { | ||
| 272 | "display_name": "sumo", | 329 | "display_name": "sumo", | ||
| 273 | "id": "266e4bda-ee60-47fb-8b86-e7d96400e827", | 330 | "id": "266e4bda-ee60-47fb-8b86-e7d96400e827", | ||
| 274 | "name": "sumo", | 331 | "name": "sumo", | ||
| 275 | "state": "active", | 332 | "state": "active", | ||
| 276 | "vocabulary_id": null | 333 | "vocabulary_id": null | ||
| 277 | }, | 334 | }, | ||
| 278 | { | 335 | { | ||
| 279 | "display_name": "trafico-vehicular", | 336 | "display_name": "trafico-vehicular", | ||
| 280 | "id": "f5618c32-be7f-4a27-aed8-18dc33db87df", | 337 | "id": "f5618c32-be7f-4a27-aed8-18dc33db87df", | ||
| 281 | "name": "trafico-vehicular", | 338 | "name": "trafico-vehicular", | ||
| 282 | "state": "active", | 339 | "state": "active", | ||
| 283 | "vocabulary_id": null | 340 | "vocabulary_id": null | ||
| 284 | }, | 341 | }, | ||
| 285 | { | 342 | { | ||
| 286 | "display_name": "transporte-urbano", | 343 | "display_name": "transporte-urbano", | ||
| 287 | "id": "7eca4c53-c436-4b41-be1f-4a5a1628a4fa", | 344 | "id": "7eca4c53-c436-4b41-be1f-4a5a1628a4fa", | ||
| 288 | "name": "transporte-urbano", | 345 | "name": "transporte-urbano", | ||
| 289 | "state": "active", | 346 | "state": "active", | ||
| 290 | "vocabulary_id": null | 347 | "vocabulary_id": null | ||
| 291 | }, | 348 | }, | ||
| 292 | { | 349 | { | ||
| 293 | "display_name": "visualizacion-de-datos", | 350 | "display_name": "visualizacion-de-datos", | ||
| 294 | "id": "8cfefa81-ab60-4188-b38b-09135f8bb70c", | 351 | "id": "8cfefa81-ab60-4188-b38b-09135f8bb70c", | ||
| 295 | "name": "visualizacion-de-datos", | 352 | "name": "visualizacion-de-datos", | ||
| 296 | "state": "active", | 353 | "state": "active", | ||
| 297 | "vocabulary_id": null | 354 | "vocabulary_id": null | ||
| 298 | }, | 355 | }, | ||
| 299 | { | 356 | { | ||
| 300 | "display_name": "visualizacion-geoespacial", | 357 | "display_name": "visualizacion-geoespacial", | ||
| 301 | "id": "2c03b847-6dbc-42f1-b2d0-e4666627ed2e", | 358 | "id": "2c03b847-6dbc-42f1-b2d0-e4666627ed2e", | ||
| 302 | "name": "visualizacion-geoespacial", | 359 | "name": "visualizacion-geoespacial", | ||
| 303 | "state": "active", | 360 | "state": "active", | ||
| 304 | "vocabulary_id": null | 361 | "vocabulary_id": null | ||
| 305 | }, | 362 | }, | ||
| 306 | { | 363 | { | ||
| 307 | "display_name": "webgl", | 364 | "display_name": "webgl", | ||
| 308 | "id": "667ddd0e-012d-417d-9e85-f8695fac9d29", | 365 | "id": "667ddd0e-012d-417d-9e85-f8695fac9d29", | ||
| 309 | "name": "webgl", | 366 | "name": "webgl", | ||
| 310 | "state": "active", | 367 | "state": "active", | ||
| 311 | "vocabulary_id": null | 368 | "vocabulary_id": null | ||
| 312 | } | 369 | } | ||
| 313 | ], | 370 | ], | ||
| 314 | "title": "Simulaci\u00f3n SUMO de Tr\u00e1fico Vehicular en el | 371 | "title": "Simulaci\u00f3n SUMO de Tr\u00e1fico Vehicular en el | ||
| 315 | Centro de Quer\u00e9taro", | 372 | Centro de Quer\u00e9taro", | ||
| 316 | "type": "dataset", | 373 | "type": "dataset", | ||
| 317 | "url": | 374 | "url": | ||
| 318 | ualizacion.observatoriogeo.mx/sylvereyesumo/dashboard/sylvereyesumo/", | 375 | ualizacion.observatoriogeo.mx/sylvereyesumo/dashboard/sylvereyesumo/", | ||
| 319 | "version": null | 376 | "version": null | ||
| 320 | } | 377 | } |
