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/26221/?format=api

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

{
    "ob_id": 26221,
    "uuid": "b43ce022c8f94f79b5c3b3ede7aad975",
    "title": "DEMON: Simulation output from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observations into the Lisflood-FP flood forecast model ",
    "abstract": "This dataset contains simulation results from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observation into Lisflood-FP flood forecast model for the the lower Severn-Avon rivers in the South West United Kingdom. This was run over a 30.6 x 49.8 km (1524 km2) domain, as part of Developing enhanced impact models for integration with next generation NWP and climate outputs (DEMON) project (NE/I005242/1).\r\n\r\nCOSMO-Skymed Synthetic Aperture Radar (CSK-SAR) data were acquired processed and transformed into Water Level Observations (WLOs) by crossing with LiDAR Digital Terrain Model. Data from Environment Agency (EA) rain gauges were used to estimate precipitation and combined with potential evapotranspiration data from the Met Office's Met Office Rainfall and Evapo-transpiration Calculation System (MORECS) to generate forcings within the \"topHSPF\" catchment-scale rainfall-runoff hydrologic model. These were used in tern to generate simulated runoff forecast used as the forcing for the coupled Lisflood-FP v5.9 inundation model. \r\n\r\nCSK-SAR based WLO were assimilated into ensemble simulations using the Lisflood-FP v5.9 model, run with perturbed physics (friction parameters, bathymetric errors) and runoff inputs from the topHSPF hydrologic model",
    "keywords": "DEMON, Synthetic Aperture Radar, Flood forecast, Assimilation, Ensemble Kalman Filter",
    "publicationState": "citable",
    "dataPublishedTime": "2018-06-28T13:11:37",
    "doiPublishedTime": null,
    "updateFrequency": "notPlanned",
    "status": "completed",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/26280/?format=api",
        "dataPath": "/badc/deposited2018/demon",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 9742783131,
        "numberOfFiles": 458,
        "fileFormat": "Data are R binary formatted"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/7082/?format=api",
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2234/?format=api",
    "nonGeographicFlag": false,
    "phenomena": [],
    "dataLineage": "Data were delivered by the project team to be archived at the Centre for Environmental Data Analysis (CEDA)",
    "removedDataTime": null,
    "removedDataReason": "",
    "language": "English",
    "identifier_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/9619/?format=api"
    ],
    "projects": [
        "https://api.catalogue.ceda.ac.uk/api/v2/projects/26219/?format=api"
    ],
    "observationcollection_set": [],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109670/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109666/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109667/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109668/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109669/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109672/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109673/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109674/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/109671/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/168824/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/110279/?format=api"
    ],
    "procedureAcquisition": null,
    "procedureCompositeProcess": null,
    "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/26220/?format=api",
    "permissions": [
        {
            "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api",
            "useLimitation": null,
            "accessConstraints": null,
            "accessCategory": "public",
            "accessRoles": null,
            "label": "public: None group",
            "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
            "licenceClassifications": "any"
        }
    ],
    "discoveryKeywords": [
        {
            "ob_id": 1138,
            "name": "NDGO0003"
        }
    ]
}