Observation Instance
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/39606/?format=api
{ "ob_id": 39606, "uuid": "9c41e3aa67024bbdad796290a861e968", "title": "Large ensemble of global mean temperatures: 6-hourly HadAM4 model run data using the Climateprediction.net platform", "abstract": "Large ensembles of global temperature are provided for three climate scenarios: historical (2006-16), 1.5 C and 2.0 C above pre-industrial levels. Each scenario has 700 members (70 runs per year for 10-year periods) of 6-hourly mean temperatures at a resolution of 0.833 degrees x 0.556 degrees (longitude x latitude). The data was generated using the climateprediction.net (CPDN) climate simulation environment, to run the Met Office HadAM4 Atmosphere-only General Circulation Model (AGCM) from the UK Met Office Hadley Centre. Biases in simulated temperature were identified and corrected using quantile mapping with reference temperature data from ERA5 reanalysis. \r\n\r\nData were generated using the Met Office HadAM4 model at 6-hourly temporal resolution and 0.833 degrees x 0.556 degrees (longitude x latitude) over global domain. The data from each scenario is divided into 4 batches. Historic scenario (2006-2016): December-March data in Batch 889, April-May data in Batch 920, June-September data in Batch 901, October-November data in Batch 923. 1.5C scenario: December-March data in Batch 891, April-May data in Batch 921, June-September data in Batch 902, October-November data in Batch 924. 2.0C scenario: December-March data in Batch 895, April-May data in Batch 922, June-September data in Batch 903, October-November data in Batch 925.", "keywords": "HadAM4, Climateprediction.net", "publicationState": "citable", "dataPublishedTime": "2023-06-26T14:36:29", "doiPublishedTime": "2023-06-28T13:55:34.179546", "updateFrequency": "notPlanned", "status": "completed", "result_field": { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/39607/?format=api", "dataPath": "/badc/deposited2023/CPDN_HadAM4", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1698725532892, "numberOfFiles": 8401, "fileFormat": "NetCDF" }, "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10973/?format=api", "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api", "nonGeographicFlag": false, "phenomena": [ "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62607/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62608/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62609/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62610/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62611/?format=api" ], "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12536/?format=api" ], "projects": [ "https://api.catalogue.ceda.ac.uk/api/v2/projects/39604/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/projects/39605/?format=api" ], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193044/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193045/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193046/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193047/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193048/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193049/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193050/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193057/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193051/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193052/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193053/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193054/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193055/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/193056/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/40180/?format=api", "permissions": [ { "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2521/?format=api", "useLimitation": null, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": "unstated" } ], "discoveryKeywords": [] }