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/39572/?format=api

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

{
    "ob_id": 39572,
    "uuid": "b21d053ef801467298cf87811467a7eb",
    "title": "RisesAM-OceanWaves:  An hourly simulation of sea surface waves for historic and future climate",
    "abstract": "This data collection comprises four simulations; covering two different domains and two different periods. RisesAM-NEA is a regional model of the North East Atlantic, and RisesAM-Global covers the world ocean. Each simulation is run for a historic reanalysis period (1979-2015) forced by ECMWF Re-Analysis winds (ERA-Interim, https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-interim) The global models are also forced with sea-ice cover from the same data source. The climate projections (1970-2100) are forced by EC-Earth (https://ec-earth.org/) Regional models are driven by the same climate models, downscaled to 12km resolution, under EuroCordex programme (https://euro-cordex.net/) The data are produced with a spectral wave model; WaveWatchIII (Tolman, 1997). The data on a regular lat/long grid and the global wave model resolution is around 0.8 degrees, and the regional model is 1/12th degree. The netcdf data include high frequency (hourly) wave data of bulk parameters representing significant wave height, mean wave direction, and energy period. Partitioned wave data are also included for significant wave height, peak period, and direction. These data are presented in 3 partitions, with a fraction of wind sea specified for each. The data set is produced to investigate the future wave conditions of Europe under climate change. There are 2 different climate futures explored; RCP8.5 and RCP4.5 (regional concentration pathways). The simulations were run using funding from the European Union’s Seventh Programme for Research, Technological Development and Demonstration under Grant Agreement No: FP7-ENV-2013-Two-Stage-603396-RISES-AM-. This work used the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk)",
    "keywords": "surface, model, wave, ERA, interim, reanalysis, UK, climate, projections, UKCP18",
    "discoveryKeywords": [],
    "publicationState": "published",
    "dataPublishedTime": "2023-04-04T13:47:30",
    "doiPublishedTime": null,
    "member": [
        "https://api.catalogue.ceda.ac.uk/api/v2/observations/39560/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/observations/39564/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/observations/39566/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/observations/39570/?format=api"
    ],
    "identifier_set": [],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192975/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192973/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192976/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192971/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192978/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192970/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192974/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192972/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/192977/?format=api"
    ]
}