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/32809/?format=api

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

{
    "ob_id": 32809,
    "uuid": "f088e7a33a25409197ea9b6aa3b90864",
    "title": "CCMI-2022: refD1 data produced by the SOCOL model at ETH-PMOD",
    "abstract": "This dataset contains model data for CCMI-2022 experiment refD1 produced by the SOCOL (SOlar Climate Ozone Links) model run by the modelling team at ETH-PMOD (Swiss Federal Institute of Technology Zurich and the Physical-Meteorology Observatory Davos).\r\n\r\nThe refD1 experiment is a hindcast of the atmospheric state, using a prescribed evolution of sea surface temperature and sea ice from observations along with forcings for the extra-terrestrial solar flux, long-lived greenhouse gases and ozone depleting substances, stratospheric aerosols and an imposed quasi-biennial oscillation that approximate the observed variations over the historical period to the fullest extent possible.\r\n\r\nThe CCMI-2022 Chemistry-climate model initiative is a set of model experiments focused on the stratosphere, with the goals of providing updated projections towards the future evolution of the ozone layer and improving our understanding of chemistry-climate interactions from models.\r\n\r\n------------------------------------------\r\nSources of additional information\r\n------------------------------------------\r\nThe following web links are provided in the Details/Docs section of this catalogue record:\r\n-  Atmosphere-Ocean-Aerosol-Chemistry-Climate Model SOCOLv4.0: description and evaluation.\r\n-  A new set of Chemistry-Climate Model Initiative (CCMI) Community Simulations to Update the Assessment of Models and Support Upcoming Ozone Assessment Activities, David Plummer and Tatsuya Nagashima and Simone Tilmes and Alex Archibald and Gabriel Chiodo and Suvarna Fadnavis and Hella Garny and Beatrice Josse and Joowan Kim and Jean-Francois Lamarque and Olaf Morgenstern and Lee Murray and Clara Orbe and Amos Tai and Martyn Chipperfield and Bernd Funke and Martin Juckes and Doug Kinnison and Markus Kunze and Beiping Luo and Katja Matthes and Paul A. Newman and Charlotte Pascoe and Thomas Peter (2021), SPARC Newsletter, volume 57, pp 22-30",
    "keywords": "CCMI-2022, refD1, Hindcast, Scenario, SOCOL, ETH-PMOD, APARC",
    "publicationState": "published",
    "dataPublishedTime": "2024-11-11T15:47:52",
    "doiPublishedTime": null,
    "updateFrequency": "",
    "status": "completed",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32806/?format=api",
        "dataPath": "/badc/ccmi/data/post-cmip6/ccmi-2022/ETH-PMOD/SOCOL/refD1",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 361060547370,
        "numberOfFiles": 426,
        "fileFormat": "netCDF"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/9009/?format=api",
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/1/?format=api",
    "nonGeographicFlag": false,
    "phenomena": [
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6021/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6022/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6023/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50415/?format=api",
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        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50418/?format=api",
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        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50420/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50421/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50422/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50423/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50424/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50425/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50426/?format=api",
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        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50439/?format=api",
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        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50446/?format=api",
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        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50457/?format=api",
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        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50463/?format=api",
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        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/71572/?format=api",
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        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/71619/?format=api",
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        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/74528/?format=api"
    ],
    "dataLineage": "Data were generated using the SOCOLv4.0 model at T63 horizontal resolution over the global domain. CCMI-2022 data has been converted to CF-netCDF by the model team using CDO and CMOR3 then passed on to the CEDA for archiving.",
    "removedDataTime": null,
    "removedDataReason": "",
    "language": "English",
    "identifier_set": [],
    "projects": [
        "https://api.catalogue.ceda.ac.uk/api/v2/projects/32805/?format=api"
    ],
    "observationcollection_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/32820/?format=api"
    ],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/146497/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/146498/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/146499/?format=api",
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        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/146501/?format=api",
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    ],
    "procedureAcquisition": null,
    "procedureCompositeProcess": null,
    "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/32808/?format=api",
    "permissions": [
        {
            "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2544/?format=api",
            "useLimitation": null,
            "accessConstraints": null,
            "accessCategory": "restricted",
            "accessRoles": "ccmi-2022",
            "label": "restricted: ccmi-2022 group",
            "licenceURL": "https://artefacts.ceda.ac.uk/licences/rugl_versions/rugl_v1-0.pdf",
            "licenceClassifications": "any"
        }
    ],
    "discoveryKeywords": []
}