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/40016/?format=api

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

{
    "ob_id": 40016,
    "uuid": "bd375134bd8c4990a1e9eb6d199cc723",
    "title": "Physical Marine Climate Projections for the North West European Shelf Seas: EnsStats",
    "abstract": "Ensemble statistics are calculated from the North West Shelf Perturbed Parameter Ensemble (NWSPPE) climatologies. The NWSPPE (https://catalogue.ceda.ac.uk/uuid/edf66239c70c426e9e9f19da1ac8ba87) provides climatological mean and climatological standard deviations for an early-century period (2000-2019) and a late-century period (2079-2098) for each of the 12 NWSPPE ensemble members, for the annual means, and for each month and season of the year. These have been processed into ensemble statistics, for each period (2000-2019, 2079-2098, and the difference 2079-2098minus2000-2019), and for each season and month and for annual means. For the early-century and late-century climatology periods, these ensemble statistics include the ensemble mean, ensemble variance, ensemble standard deviation and interannual variance. These describe the behaviour of the ensemble, including any present day ensemble spread. For the statistics of the difference between the periods (2079-2098minus2000-2019), we simply provide the difference between the ensemble statistics calculated in the near present and end of century period. To allow the user to simply use these data to provide projections, with the associated uncertainty, we also provide two additional statistics, the projected ensemble mean (projensmean) and the projected ensemble standard deviation (projensstd). We remove the early-century climatological mean from the late-century climatological mean, for each ensemble member of the NWEPPE to give an anomaly ensemble. We then calculate the resulting ensemble mean (projensmean) and its standard deviation (projensstd).\r\n\r\nNucleus for European Modelling of the Ocean (NEMO) has three model grids, the T, U and V grids, and we output variables in three files, respecting their native model grid. In practice, all our variables are on the T grid, apart from the Eastward and Northward components of the depth mean velocities (DMU, DMV), which are in the U and V grid files respectively. The T grid files have Sea Surface, Near Bed, and the Difference between the surface and bed Temperature and Salinity (SST, NBT, DFT, SSS, NBS, DFS), Potential Energy Anomaly (PEA), Mixed Layer Depth (MLD), the barotropic current magnitude interpolated onto the T grid (DMUV).",
    "keywords": "UKCP, Marine Climate, Uncertainty, Climate Downscaling, NW European Shelf Seas, Shelf Seas, Temperature, SST, Salinity, Stratification, North Sea, Celtic Sea, Irish Sea, English Channel",
    "publicationState": "citable",
    "dataPublishedTime": "2023-06-01T13:25:08",
    "doiPublishedTime": "2023-07-20T16:33:11",
    "updateFrequency": "",
    "status": "completed",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/40063/?format=api",
        "dataPath": "/badc/deposited2023/marine-nwsclim/EnsStats",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 1296272351,
        "numberOfFiles": 154,
        "fileFormat": "Data are provided in NetCDF format."
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11077/?format=api",
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/3815/?format=api",
    "nonGeographicFlag": false,
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    ],
    "dataLineage": "The UKCP18 HadGEM3 GC3.05 Perturbed Parameter Ensemble was dynamically downscaled with shelf seas climate version of NEMO 4.0.4 (CO9) to give a set of climate projections.\r\n \r\nModel output from HadGEM3 GC3.05 was processed into model input for CO9. CO9 was run for each of the 12 ensemble members as transient simulations. The results were assessed against a range of observations, which will be described  in Tinker et al. (2023, in prep). The model output was then post-processed into ensemble statistics using the python package available at https://github.com/hadjt/NWS_simulations_postproc. After data and code evaluation, the dataset was supplied for archiving at the Centre for Environmental Data Analysis (CEDA).",
    "removedDataTime": null,
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    "language": "English",
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}