Last modified by Vincent Massol on 2024/02/26 17:51

From version 17.2
edited by slauriere
on 2019/05/28 14:33
Change comment: There is no comment for this version
To version 19.1
edited by slauriere
on 2019/05/28 14:44
Change comment: There is no comment for this version

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105 105  
106 106  In order to implement the use cases described above, at some point that will be useful to work with a significant amount of data. This paragraph is about gathering such data. This step can come later in the process, once the basic structure is implemented and a workable prototype is working with data entered manually.
107 107  
108 -Open data sources of geolocalized data:
109 -* OpenStreetMap: choose a large city, download shapes, transports, paths related to that city
108 +=== OpenStreetMap ===
109 +
110 +==== List of memorials ====
111 +
112 +URL: https://overpass-turbo.eu/
113 +
114 +Choose a large city, enter the query below, then export it into GeoJSON:
115 +
116 +{{code}}
117 +node
118 + [historic=memorial]
119 + ({{bbox}});
120 +out;
121 +{{/code}}
122 +
123 +=== Other data sources ===
124 +
110 110  * Wikidata: choose a large city, see what gelocalized data we can retrieve for that city: monuments, points of interests...
111 111  * Paris Open Data:
112 -*** [[https:~~/~~/opendata.paris.fr/>>https://opendata.paris.fr/]]
113 -*** [[https:~~/~~/opendata.stif.info/explore/>>https://opendata.stif.info/explore/]]
114 -*** [[https:~~/~~/data.ratp.fr/>>https://data.ratp.fr/]]
127 +** [[https:~~/~~/opendata.paris.fr/>>https://opendata.paris.fr/]]
128 +** [[https:~~/~~/opendata.stif.info/explore/>>https://opendata.stif.info/explore/]]
129 +** [[https:~~/~~/data.ratp.fr/>>https://data.ratp.fr/]]
115 115  
116 116  
117 117  == Mockups ==

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