Observation Instance – Django REST framework

Get a list of Observation objects.

### Available end points:

- `/observations/` - Will list all Results in the database
- `/observations.json` - Will return all Results in json format. This can
also be achieved by using the accept header. `application/json`
- `/observations/<object_id>/` - Returns Results object with that id

### Available Methods:

- `GET`
- `HEAD`

### Available filters:

- `title`
- `uuid`
- `keywords`
- `status`
- `result_field`
- `discoveryKeywords`
- `updateFrequency`
- `nonGeographicFlag`
- `publicationState`
- `permissions`

### How to use filters:

These filters can be used like django query filters using __ for related model relationships.

- `/observations/?uuid=d594d53df2612bbd89c2e0e770b5c1a0`
- `/observations/?status=completed`
- `/observations/?results_field__dataPath__startswith=/neodc/esacci`
- `/observations/?discoveryKeywords__name=ESACCI`
- `/observations/?nonGeographicFlag=True`

Filters can be stacked to build an 'AND' relationship. E.g.

- `/observations/?publicationState__in=published,citable&nonGeographicFlag=True`
- `/observations/?publicationState__in=published,citable&discoveryKeyword__name=NDGO0003`

GET /api/v2/observations/41248/?format=api

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

{
    "ob_id": 41248,
    "uuid": "a9f48ce8418748119c6886a07b8e232f",
    "title": "Model output containing ocean and sea ice variables from GOSI9 eORCA025 (1976-2005)",
    "abstract": "This dataset contains monthly and annual means of ocean and sea ice variables from a 30 year (1976-2005) integration of the GOSI9 model configuration at 1/4° horizontal resolution. The ocean output fields on T, U, V, and W grids are provided in separate files. The ocean component is on a 1/4° grid (eORCA025) with 75 vertical levels. The sea ice data is on the ocean T grid with 5 thickness categories. GOSI9 is the latest version of the global ocean-sea ice configuration developed under the Joint Marine Modelling Programme (JMMP). The temperature and salinity fields were initialised from EN4 climatology (Good et al., 2013) and forced by the CORE2 surface dataset (Large &amp; Yeager, 2009). All initialisation and ancillary data are also included. The data were generated under the Climate Linked Atlantic Sector Science (CLASS) project funded by the Natural Environment Research Council (NERC).",
    "keywords": "oceans, geoscientificInformation",
    "publicationState": "citable",
    "dataPublishedTime": "2023-12-12T16:28:13",
    "doiPublishedTime": "2023-12-12T16:28:13",
    "updateFrequency": "",
    "status": "final",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/41247/?format=api",
        "dataPath": "/bodc/SOC230182/",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 4001118893075,
        "numberOfFiles": 2664,
        "fileFormat": "NetCDF, text"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11455/?format=api",
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/4072/?format=api",
    "nonGeographicFlag": false,
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