Interoperability

Stephan Schildberg edited this page Jan 18, 2018 · 4 revisions

French translation: Interopérabilité

In the following diagram, we can see an overview of the whole project on the interoperability of Communecter with various sources.

Diagram of the interoperability of Communecter with various sources

On the left is the list of external sources on which the data are retrieved :

  • Wikidata
  • Wikipedia
  • OpenStreetMap
  • OpenDataSoft (the SIRENE database)
  • Data.gouv
  • Datanova (signs of La Poste)
  • Pôle Emploi
  • SCANR (scanR, moteur de la recherche et de l'innovation )

In the middle, the Data Conversion process (details on next figure)

On the right, the display of the data converted on the site of Communecter as well as examples of use of these data by external sites.

The following diagram describes in detail the conversion of the semantic data.

Semantic Conversion Detail

We interoperate with

using their API

Wikidata

For any city, We retrieve main information available on Wikidata

The process is the following :

  • We choose a geographic scope (a country) to filter
  • We call our own semantic convert system (doc available here) :

The convert system will interrogate the Wikidata API to get data in JSON.

The next example is the data for the city of Saint-Denis, capital city of Réunion island :

https://query.wikidata.org/sparql?format=json&query=SELECT%20DISTINCT%20%3Fitem%20%3FitemLabel%20%3FitemDescription%20%3Fcoor%20%3Frange%20WHERE%20{%0A%20%3Fitem%20wdt%3AP131%20wd%3AQ47045.%0A%20%3Fitem%20%3Frange%20wd%3AQ47045.%0A%20%3Fitem%20wdt%3AP625%20%3Fcoor.%0A%20SERVICE%20wikibase%3Alabel%20{%20bd%3AserviceParam%20wikibase%3Alanguage%20%22fr%22.%20}%0A}

And convert this data in the pivot language named "PH onthology"

/ph/api/convert/wikipedia?url=https://www.wikidata.org/wiki/Special:EntityData/Q47045.json

Example Wikidata here

Here are the mapping

Source's data PH onthology
itemLabel.value name
coor.latitude geo.latitude
coor.longitude geo.longitude
item.value url
itemDescription.value description
  • We'll want to contributing back any extra data we can offer with COpedia (coming soon)

DBpedia

  • For any city, We retrieve main information available on Wikipedia

OpenStreetMap

For any city, we retrieve main information available on OSM

The process is the following :

  • We choose a geographic scope (a country) to filter
  • We call our own semantic convert system (doc available here) :

The next example is all the OSM data of the city of Saint-Louis :

http://overpass-api.de/api/interpreter?data=[out:json];node[%22name%22](poly:%22-21.303505996763%2055.403919253998%20-21.292626813288%2055.391189163162%20-21.282029142394%2055.381522536523%20-21.256155186265%2055.392395046639%20-21.232012804782%2055.387888015185%20-21.211100938923%2055.390619722192%20-21.199480966855%2055.382654775478%20-21.185882138486%2055.385961778627%20-21.173346518752%2055.389949958731%20-21.16327583783%2055.399563417107%20-21.14709868917%2055.405379688232%20-21.166028899095%2055.414700890276%20-21.184085220909%2055.432085218794%20-21.190290936422%2055.440880800108%20-21.195166490948%2055.462318490892%20-21.237553168259%2055.459769285867%20-21.258726107298%2055.463692709631%20-21.286021128961%2055.455515913879%20-21.294777773557%2055.419916682666%20-21.303505996763%2055.403919253998%22);out%2030;

Here are the mapping

Source's data PH onthology
tags.name name
lat geo.latitude
long geo.longitude
type type
tags.amenity tags.0

Example OSM here

  • We'll want to contribution back any extra data we can offer with COSM (coming soon)

Data.gouv

For any city, we retrieve main information of the organizations placed in this city

The process is the following :

  • We choose a geographic scope (a country) to filter
  • We call our own semantic convert system (doc available here) :

The module will find all the organizations placed in the geographic scope filter and then extract all the data in the different datasets available.

The next example is all the data of the different structure of Méto-France, meteorological center of France.

https://www.data.gouv.fr/api/1/datasets/54a12162c751df720a04805a/

Here are the mapping

Source's data PH onthology
slug name
page url
tags[] tag[]
item.value url
owner creator

Example Data.gouv here

Pôle emploi

For any city, we retrieve all the job offer. (no exact localization of the job place)

The process is the following :

  • We choose a geographic scope (a country) to filter
  • We call our own semantic convert system (doc available here) :

To get data with the Pôle emploi's API, a token is needed.

The next example fetch all the job offer of the city of Saint-Louis.

https://api.emploi-store.fr/partenaire/infotravail/v1/datastore_search_sql?sql=SELECT%20%2A%20FROM%20%22421692f5-f342-4223-9c51-72a27dcaf51e%22%20WHERE%20%22CITY_CODE%22=%2797414%27%20LIMIT%2030

OpenDataSoft (SIREN database)

For any city, we retrieve all the organizations and the association of the SIREN's database.

The process is the following :

  • We choose a geographic scope (a country) to filter
  • We call our own semantic convert system (doc avaible here) :

The next example will fetch all the data in the SIRENE database for the city of Saint-Louis.

https://data.opendatasoft.com/api/records/1.0/search/?dataset=sirene%40public&facet=categorie&facet=proden&facet=libapen&facet=siege&facet=libreg_new&facet=saisonat&facet=libtefen&facet=depet&facet=libnj&facet=libtca&facet=liborigine&rows=30&start=0&geofilter.polygon=(-21.303505996763,55.403919253998),(-21.292626813288,55.391189163162),(-21.282029142394,55.381522536523),(-21.256155186265,55.392395046639),(-21.232012804782,55.387888015185),(-21.211100938923,55.390619722192),(-21.199480966855,55.382654775478),(-21.185882138486,55.385961778627),(-21.173346518752,55.389949958731),(-21.16327583783,55.399563417107),(-21.14709868917,55.405379688232),(-21.166028899095,55.414700890276),(-21.184085220909,55.432085218794),(-21.190290936422,55.440880800108),(-21.195166490948,55.462318490892),(-21.237553168259,55.459769285867),(-21.258726107298,55.463692709631),(-21.286021128961,55.455515913879),(-21.294777773557,55.419916682666),(-21.303505996763,55.403919253998)

Here are the mapping

Source's data PH onthology
fields.l1_declaree name
fields.categorie type
fields.siret shortDescription
fields.coordonnees.0 geo.latitude
fields.coordonnees.1 geo.longitude
fields.libapen tags.0

Example OpenDataSoft here

ScanR ( National Education )

For any city, we retrieve main information from the national education of France

The process is the following :

  • We choose a geographic scope (a country) to filter
  • We call our own semantic convert system (doc available here) :

The next example fetch all the actives research structures of the city of Bordeaux :

https://data.enseignementsup-recherche.gouv.fr/api/records/1.0/search/?dataset=fr-esr-etablissements-publics-prives-impliques-recherche-developpement&facet=siren&facet=libelle&facet=date_de_creation&facet=categorie&facet=libelle_ape&facet=tranche_etp&facet=categorie_juridique&facet=wikidata&facet=commune&facet=unite_urbaine&facet=departement&facet=region&facet=pays&facet=badge&facet=region_avant_2016&rows=30&start=0&geofilter.polygon=(44.810795852605,-0.5738778170842),(44.817148298105,-0.57643460444186),(44.823910193873,-0.58695822406613),(44.818476638462,-0.60304723869607),(44.822474304509,-0.61064859861704),(44.824937843733,-0.61415033833008),(44.835177466959,-0.61079419661495),(44.841384923705,-0.62771243191386),(44.860667021743,-0.63833642556746),(44.871658097695,-0.63105127891779),(44.86227970331,-0.61630176568479),(44.854215265872,-0.59460939385687),(44.865671076253,-0.57646019656194),(44.869188961886,-0.57608874140575),(44.909402227434,-0.58088555560083),(44.908480410411,-0.57648917779388),(44.916666965125,-0.54773554113942),(44.889099273803,-0.53553255107571),(44.869138522062,-0.54141014437767),(44.868086689933,-0.53680669655034),(44.861267174723,-0.53784686147751),(44.848134506953,-0.53761462401784),(44.842390488778,-0.5422310311368),(44.836291776079,-0.54665943781219),(44.829021270567,-0.53642317794196),(44.822772234064,-0.53766321563778),(44.813135278103,-0.55606047183132),(44.810795852605,-0.5738778170842)

Here are the mapping :

Source's data PH onthology
fields.libelle name
fields.site_web shortDescription
fields.geolocalisation.0 geo.latitude
fields.geolocalisation.1 geo.longitude

Example ScanR here

  • Datasets used :
    • Public or private research and development structures
    • Member of the university institute of France

Datanova ( La Poste )

For any city, we retrieve the location of all buildings of La Poste

The process is the following :

  • We choose a geographic scope (a country) to filter
  • We call our own semantic convert system (doc available here) :

The next example will fetch all La Poste buildings localized in the city of Saint-Louis.

https://datanova.laposte.fr/api/records/1.0/search/?dataset=laposte_poincont&rows=30&start=0&geofilter.polygon=(-21.303505996763,55.403919253998),(-21.292626813288,55.391189163162),(-21.282029142394,55.381522536523),(-21.256155186265,55.392395046639),(-21.232012804782,55.387888015185),(-21.211100938923,55.390619722192),(-21.199480966855,55.382654775478),(-21.185882138486,55.385961778627),(-21.173346518752,55.389949958731),(-21.16327583783,55.399563417107),(-21.14709868917,55.405379688232),(-21.166028899095,55.414700890276),(-21.184085220909,55.432085218794),(-21.190290936422,55.440880800108),(-21.195166490948,55.462318490892),(-21.237553168259,55.459769285867),(-21.258726107298,55.463692709631),(-21.286021128961,55.455515913879),(-21.294777773557,55.419916682666),(-21.303505996763,55.403919253998)

Here are the mapping

Source's data PH onthology
fields.libelle_du_site name
recordid type
fields.adresse address.streetAddress
fields.latlong.0 geo.latitude
fields.latlong.1 geo.longitude
fields.libapen tags.0

Example Datanova here

Smart Citizen (coming soon)

  • onclick : we'll show all SCK kits for a given city

Umaps (coming soon)

  • POI's of type geoJson, on click we show the content on our map

WordPress RSS (coming soon)

  • any WP blog's RSS can be plugged to an elements wall

using an iframe

FramaPads

  • users can use Framapads from inside CO(simple Iframe)
Clone this wiki locally
You can’t perform that action at this time.
You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session.
Press h to open a hovercard with more details.