The ROR API allows to retrieve, search and filter the organizations indexed in ROR. The results are returned in JSON.
A single organization record is represented by the following JSON structure:
{
"id":"https://ror.org/013cjyk83",
"name":"PSL Research University",
"email_address":null,
"ip_addresses":[
],
"established":2010,
"types":[
"Education"
],
"relationships":[
{
"label":"ESPCI Paris",
"type":"Child",
"id":"https://ror.org/03zx86w41"
},
{
"label":"Subcellular Structure and Cellular Dynamics",
"type":"Child",
"id":"https://ror.org/04w11tv37"
},
{
"label":"École Pratique des Hautes Études",
"type":"Child",
"id":"https://ror.org/046b3cj80"
}
],
"addresses":[
{
"lat":48.854692,
"lng":2.33781,
"state":null,
"state_code":null,
"city":"Paris",
"geonames_city":{
"id":2988507
8000
,
"city":"Paris",
"geonames_admin1":{
"name":"Île-de-France",
"id":3012874,
"ascii_name":"Ile-de-France",
"code":"FR.11"
},
"geonames_admin2":{
"name":"Paris",
"id":2968815,
"ascii_name":"Paris",
"code":"FR.11.75"
},
"license":{
"attribution":"Data from geonames.org under a CC-BY 3.0 license",
"license":"http://creativecommons.org/licenses/by/3.0/"
},
"nuts_level1":{
"name":"ÎLE DE FRANCE",
"code":"FR1"
},
"nuts_level2":{
"name":"Île de France",
"code":"FR10"
},
"nuts_level3":{
"name":"Paris",
"code":"FR101"
}
},
"postcode":null,
"primary":false,
"line":null,
"country_geonames_id":3017382
}
],
"links":[
"https://www.psl.eu/en/university"
],
"aliases":[
"Université PSL"
],
"acronyms":[
"PSL"
],
"status":"active",
"wikipedia_url":"https://en.wikipedia.org/wiki/PSL_Research_University",
"labels":[
{
"label":"Université de recherche Paris Sciences et Lettres",
"iso639":"fr"
}
],
"country":{
"country_name":"France",
"country_code":"FR"
},
"external_ids":{
"ISNI":{
"preferred":null,
"all":[
"0000 0004 1784 3645"
]
},
"OrgRef":{
"preferred":null,
"all":[
"31274670"
]
},
"Wikidata":{
"preferred":null,
"all":[
"Q1163431"
]
},
"GRID":{
"preferred":"grid.440907.e",
"all":"grid.440907.e"
}
}
}
This is liable to change.
The route /organizations
gives the list of all organizations.
/organizations/<ror id>
(e.g. /organizations/https://ror.org/015w2mp89
) can be used to retrieve the record of a single organization based on its ROR id.
query
parameter (e.g. /organizations?query=bath
) can be used for searching.
Note #1: Parameters query.name
and query.names
are now deprecated and redirect to query
. If you are still using them, please switch to query
, as they may be removed in the future.
Note #2: Querying is suitable for finding relevant organizations based on a few important terms. If you need to find organizations mentioned in a full affiliation string, affiliation matching will give better results.
It is possible to filter the results by type, country code or country name using filter
parameter:
/organizations?filter=types:Facility
/organizations?filter=country.country_code:GB
/organizations?filter=country.country_name:France
The filters can be combined like this: /organizations?filter=types:Facility,country.country_code:GB
. Filters can be also combined with querying.
ROR API returns 20 results per page. It is possible to iterate through the list using page
(e.g. /organizations?page=5
) parameter. It can be combined with filters and querying.
Affiliation matching allows to find organizations mentioned in the full affiliation string, such as:
Department of Civil and Industrial Engineering, University of Pisa, Largo Lucio Lazzarino 2, Pisa 56126, Italy
The URL-encoded affiliation string should be given as the affiliation
parameter:
https://api.ror.org/organizations?affiliation=Department%20of%20Civil%20and%20Industrial%20Engineering%2C%20University%20of%20Pisa%2C%20Largo%20Lucio%20Lazzarino%202%2C%20Pisa%2056126%2C%20Italy
The output contains a list of items. An item represents an organization matched to a substring of the input affiliation. The items are sorted by the matching confidence. Each item contains the information about the substring, matched organization and the matching process applied in this case:
organization
: matched ROR organization objectsubstring
: substring of the affiliation field, to which organization was matchedscore
: matching confidence score, with values between 0 and 1 (inclusive)chosen
: binary indicator of whether the score is high enough to consider the organization correctly matchedmatching_type
: type of matching algorithm applied in this case, possible values:PHRASE
: the entire phrase matched to a variant of the organization's nameCOMMON TERMS
: the matching was done by comparing the words separatelyFUZZY
: the matching was done by fuzzy-comparing the words separatelyHEURISTICS
: "University of X" was matched to "X University"ACRONYM
: matched by acronym
If you require a hard decision about which organizations are mentioned in the given affiliation string, use chosen
field. Otherwise, the resulting list can be examined in a similar manner as any search result list.
To import GRID data, you need a system where setup
has been run successfully. Then first update the GRID
variable in settings.py
, e.g.
GRID = {
'VERSION': '2020-03-15',
'URL': 'https://digitalscience.figshare.com/ndownloader/files/22091379'
}
And, also in settings.py
, set the ROR_DUMP
variable, e.g.
ROR_DUMP = {'VERSION': '2020-04-02'}
Then run this command: ./manage.py upgrade
.
You should see this in the console:
Downloading GRID version 2020-03-15
Converting GRID dataset to ROR schema
ROR dataset created
ROR dataset ZIP archive created
This will create a new data/ror-2020-03-15
folder, containing a ror.json
and ror.zip
. To finish the process, add the new folder to git and push to the GitHub repo.
To install the updated ROR data, run ./manage.py setup
.
It is possible to download the whole ROR dataset. ROR data downloads are stored here: https://github.com/ror-community/ror-api/tree/master/rorapi/data.
In the project directory, run docker-compose to start all services:
docker-compose up -d
Index the data:
docker-compose exec web python manage.py setup
and visit http://localhost:9292/organizations.
Optionally, run the tests:
docker-compose exec web python manage.py test rorapi.tests
docker-compose exec web python manage.py test rorapi.tests_integration
docker-compose exec web python manage.py test rorapi.tests_functional