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/37328/?format=api

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

{
    "ob_id": 37328,
    "uuid": "632ccda332f54b85bdb190e44ad1b493",
    "title": "ACSIS: Global ocean-ice sea ice simulations CICEv5.1.2 with prognostic melt pond model and EAP rheology with modifications including snow drift scheme, bubbly conductivity scheme, increased sea ice emissivity and reduced melt pond max fraction parameter with DFS5.2 atmospheric forcing data from 1969 - 2015",
    "abstract": "This dataset includes model output from a forced ocean-ice simulation to document the impact of sea ice physics and atmospheric forcing data on the Arctic sea ice evolution produced for the The North Atlantic Climate System Integrated Study (ACSIS). This simulation uses the same sea ice model CICE configuration GSI8.1 (Ridley et al., 2018) and the ocean-ice ones the same ocean model NEMO GO6.0 (Storkey et al., 2018) as HadGEM3. The atmospheric forcing data set are applied: DFS5.2 (Dussin et al., 2016). Regarding the sea ice component, we use the default CICE setup as in HadGEM3 (CICE-default) and an advanced setup (CICE-best) in which a new process is added (snow loss due to drifting snow) and some adjustments have been made to model physics and parameters. \r\n\r\nThe specific parameters for this dataset are:\r\nsea ice model: CICEv5.1.2 with prognostic melt pond model and EAP rheology, but with several modifications including snow drift scheme, bubbly conductivity scheme, increased sea ice emissivity and reduced melt pond max fraction parameter (see Schroeder et al., TC 2019)\r\nocean model: NEMOv3.6\r\nperiod: 1969-2015\r\natmospheric forcing: DFS5.2 (Drakkar)\r\ndomain: global\r\ngrid resolution: 0.25deg ORCA\r\n\r\nThe simulation was performed by the Centre of Polar Observation and Modelling (CPOM) at University of Reading under the ACSIS project. ACSIS was funded by the Natural Environment Research Council (NERC) through National Capability Long Term Science Multiple Centre (NC LTS-M) grant NE/N018028/1.",
    "keywords": "NEMO, CICE, ocean-ice, sea-ice, DFS5.2",
    "publicationState": "published",
    "dataPublishedTime": "2022-05-26T13:46:54",
    "doiPublishedTime": null,
    "updateFrequency": "notPlanned",
    "status": "ongoing",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/37329/?format=api",
        "dataPath": "/badc/acsis/cpom-model-sea-ice/data/NEMOCICE2018_ORCA025_1969_2015_DFS5.2_CICECPOM",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 129317544210,
        "numberOfFiles": 487,
        "fileFormat": "Files are NETCDF formatted"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10308/?format=api",
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    "nonGeographicFlag": false,
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    "language": "English",
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}