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/33226/?format=api

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

{
    "ob_id": 33226,
    "uuid": "4c545155dfd145a1b02a5d0e577ae37d",
    "title": "Monthly ocean and sea-ice output from 1/4° NEMO GO6 integration forced by JRA55 data",
    "abstract": "Monthly output from an integration of the UK Global Ocean, GO6, configuration of the NEMO (Nucleus for European Modelling of the Ocean) ocean and sea-ice model, forced by the JRA-55 (Japanese 55-year atmospheric reanalysis: Tsujino, 2018) surface field dataset. GO6 consists of version 3.6 of NEMO and version 5.2.1 of the CICE (Community Ice CodE) sea-ice model, and the present simulation is on the global eORCA025 1/4° grid. The ocean is initialised from a climatology based on the EN3 monthly objective analysis (Ingleby and Huddleston, 2007) averaged over years 2004–2008, and is integrated from 1958 to 2020. The sea-ice fields are only available for the period 1989 to 2001. The model was run on the Archer supercomputing platform through the Rose/Cylc interface on Puma, and the run ID on the Puma system is u-ba494.\t\t\r\nThe integrations were funded by the Natural Environment Research Council (NERC) under the Atlantic Climate System Integrated Study (ACSIS) project (NE/N018044/1).",
    "keywords": "Oceans, sea-ice, temperature, salinity",
    "publicationState": "citable",
    "dataPublishedTime": "2021-10-22T15:03:30",
    "doiPublishedTime": "2021-10-28T12:36:09",
    "updateFrequency": "notPlanned",
    "status": "completed",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/33252/?format=api",
        "dataPath": "/bodc/SOC210130/JRA55-BA494",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 3215771465031,
        "numberOfFiles": 3176,
        "fileFormat": "CF Compliant NetcDF"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/9134/?format=api",
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2868/?format=api",
    "nonGeographicFlag": false,
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