Observation Collection Instance – Django REST framework

Get a list of Collections objects. Collections have a 1:1 mapping with Observations.

### Available end points:

- `/observationcollections/` - Will list all Collections in the database
- `/observationcollections.json` - Will return all Collections in json format
- `/observationcollections/<object_id>/` - Returns Collections object with that id

### Available Methods:

- `GET`
- `HEAD`

### Available filters:

- `uuid`
- `title`
- `keywords`
- `discoveryKeywords`
- `publicationState`

### How to use filters:

- `/observationcollections/?uuid=ab4ca8d019d148f78afba1cd20872bdd`

- `/observationcollections.json?publicationState=citable`

GET /api/v2/observationcollections/45715/?format=api

HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 45715,
    "uuid": "293b18f4c0e348e2a55c46d94e8f2b15",
    "title": "NERC Airborne Research Facility (NERC-ARF) Remote Sensing Data",
    "abstract": "Natural Environment Research Council's Airborne Research Facility (NERC-ARF) extends the work of the NERC The Airborne Research & Survey Facility (ARSF) which itself was formerly the Airborne Remote Sensing Facility.  It provides the UK environmental science community, and other potential users, with the means to obtain remotely-sensed data in the form of digital imagery, hyperspectral and lidar, for use in research, survey and monitoring programmes. Occasionally in-situ instruments were also included. Data offered by the facility includes: \r\n\r\n1)digital photography data collected using a Leica RCD105 camera, \r\n2)hyperspectral data collected using a Specim Aisa FENIX imager\r\n3)hyperspectral data collected using a Specim Aisa OWL imager\r\n4)full-waveform airborne LiDAR data collected using a Leica ALS50II LiDAR\r\n\r\nThis collection contains data from instruments are carried on the British Antarctic Survey (BAS) twin-otter aircraft from 2017 to 2019.",
    "keywords": "NERC, ARF, LiDAR, EAGLE, HAWK, OWL, BAS",
    "discoveryKeywords": [],
    "publicationState": "preview",
    "dataPublishedTime": null,
    "doiPublishedTime": null,
    "member": [
        "https://catalogue.ceda.ac.uk/api/v2/observations/32272/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/observations/32277/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/observations/32320/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/observations/45691/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/observations/45695/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/observations/45699/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/observations/45703/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/observations/45707/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/observations/45711/?format=api"
    ],
    "identifier_set": [],
    "responsiblepartyinfo_set": [
        "https://catalogue.ceda.ac.uk/api/v2/rpis/218454/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/218450/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/218451/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/218452/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/218453/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/218456/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/218457/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/218459/?format=api"
    ]
}