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/37662/?format=api

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

{
    "ob_id": 37662,
    "uuid": "7668ea6b334841b0b7a06c0545664858",
    "title": "Regional summaries from Arctic high-resolution sea ice-ocean modelling hindcasts (2008-2021)",
    "abstract": "Regional summaries from the high-resolution sea ice-ocean modelling ERA5JRA55-forced hindcasts (Japanese 55-year atmospheric analysis) were generated to analyse oceanic impacts on retreat of the Arctic sea-ice pack in the high Arctic and from areas of the Transpolar drift, north of Greenland and in the Fram Strait in the present climate. The model outputs span the Arctic Ocean proper and the sub-Arctic seas, covering the near-present climate period from 2008-2021 during which the largest sea ice changes have been observed.\r\n\r\nThe model configuration is Global Ocean and Sea Ice GO8p7, developed under the Joint Marine Modelling Programme (JMMP), a collaborative project between the National Oceanography Centre (NOC), British Antarctic Survey (BAS) and the Met Office. GO8p7 is based on NEMO v4.0 and the SI3 sea ice model and includes a package of modifications intending to address errors in the Southern Ocean, including a scale-dependent Gent & McWilliams parameterisation, partial slip lateral boundary conditions south of 50°S. and 4th-order horizontal tracer advection (Madec et al. 2019).\r\n\r\nThe present simulation was integrated with Japanese Reanalysis JRA55 v1.3-do from 1958 to 2021 (Tsujino et al., 2018).  The model output has been validated against AMSR-E satellite sea-ice concentrations, as well as the CryoSat-2 and SMOS sea-ice thickness datasets. The monthly and 5-day averages of the key sea-ice and ocean fields for the pan-Arctic and Greenland regions were created and combined into 4-D files for easy data handling.\r\n\r\nThe model output has been validated against AMSR-E satellite sea-ice concentrations, as well as the CryoSat-2 and SMOS sea-ice thickness datasets. The monthly and 5-day averages of the key sea-ice and ocean fields for the pan-Arctic and Greenland regions were created and combined into 4-D files for easy data handling. \r\n\r\nThe model datasets were produced by National Oceanography Centre (NOC) scientists Dr Yevgeny Aksenov and Dr Stefanie Rynders, using the global model runs carried out by Dr Alex Megann. Dr Andrew Coward also assisted with data handling. The data were produced under Natural Environment Research Council (NERC) project PRE-MELT (grant references NE/T001399/1, NE/T000260/1, NE/T000546/1). The global model integrations were completed thanks to the funding from the National Environmental Research Council (NERC) national capability grant for the North Atlantic Climate System: Integrated study (ACSIS) NCLTS-M program (grant NE/N018044/1) (Megann et al., 2022a,b).  Additional funding also came from NERC projects APEAR (grant reference NE/R012865/1) and CLASS (grant reference NE/R015953/1).",
    "keywords": "Arctic Ocean, sea-ice, JRA55 v1.3-do, GO8p7, Fram Strait, CryoSat-2, SMOS, ARCRegiH",
    "publicationState": "published",
    "dataPublishedTime": "2023-08-21T14:31:22",
    "doiPublishedTime": null,
    "updateFrequency": "notPlanned",
    "status": "completed",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/37663/?format=api",
        "dataPath": "/bodc/SOC220091/PRE-MELT_hindcasts",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 511780457950,
        "numberOfFiles": 20,
        "fileFormat": "Data are CF-compliant NetCDF formatted data files"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10395/?format=api",
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    "nonGeographicFlag": false,
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    ],
    "dataLineage": "Model hindcasts were produced by scientists at the National Oceanography Centre (NOC), Southampton, UK. Outputs suitable for re-use were uploaded by the scientists to the Centre for Environmental Data Analysis (CEDA) ingestion area, where the British Oceanographic Data Centre (BODC) carried out ingestion process, creating catalogue records and making the data available for public download.",
    "removedDataTime": null,
    "removedDataReason": "",
    "language": "English",
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}