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/33235/?format=api

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

{
    "ob_id": 33235,
    "uuid": "eaec37f29d234843bfd50accee2de0d0",
    "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): Collection of datasets of altimeter along-track high resolution sea level anomalies and associated trends in some coastal regions, v1.1",
    "abstract": "This dataset collection contains various along-track sea level anomaly products derived from satellite altimetry by the ESA Sea Level Climate Change Initiative project.\r\n\r\nTwo datasets containing along-track sea level anomalies derived from satellite altimetry have been derived; one containing data from the JASON satellites (JASON-1, JSON-2, and JSON-3), and the other from the RA2 instrument on ENVISAT and the Altika instrument on SARAL satellite missions.\r\n\r\nThese have been processed to produce high resolution (20 Hz, corresponding to an along-track distance of ~300m) sea level anomalies, in order to provide long-term homogeneous sea level time series as close to the coast as possible in six different coastal regions (North-East Atlantic, Mediterranean Sea, Western Africa, North Indian Ocean, South-East Asia and Australia).  \r\n\r\nThe products benefits from the spatial resolution provided by high-rate data, the Adaptive Leading Edge Subwaveform Retracker (ALES) and the post-processing strategy of the along-track (X-TRACK) algorithm, both developed for the processing of coastal altimetry data, as well as the best possible set of geophysical corrections.  \r\n\r\nAdditionally a database of coastal sea level anomalies and associated trends from Jason satellite altimetry, derived from the JASON sea level anomaly product is included.",
    "keywords": "",
    "discoveryKeywords": [],
    "publicationState": "preview",
    "dataPublishedTime": null,
    "doiPublishedTime": null,
    "member": [
        "https://api.catalogue.ceda.ac.uk/api/v2/observations/31822/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/observations/31825/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/observations/33045/?format=api"
    ],
    "identifier_set": [],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/148383/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/148384/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/148385/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/148386/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/148387/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/148388/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/148389/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/148390/?format=api"
    ]
}