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/32163/?format=api
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 32163,
    "uuid": "7ea7540135f441369716ef867d217519",
    "title": "ESA Glaciers Climate Change Initiative (Glaciers_cci):  2017 inventory of ice marginal lakes in Greenland (IIML), v1",
    "abstract": "The 2017 inventory of ice marginal lakes in Greenland (IIML) has been produced as part of the European Space Agency (ESA) Climate Change Initiative (CCI) in Option 6 of the Glaciers_cci project, and is a product that addresses the terrestrial essential climate variable (ECV) Lakes.\r\n\r\nThe IIML is a comprehensive record of all identified ice marginal lakes across the terrestrial margin of Greenland, detected using remote sensing techniques. The detected lakes are presented as polygon vector features in shapefile format, with coordinates provided in the WGS 1984 UTM Zone 24N projected coordinate system. Ice marginal lakes were identified using three independent remote sensing methods: 1) multi-temporal backscatter classification from Sentinel-1 synthetic aperture radar imagery; 2) multi-spectral indices classification from Sentinel-2 optical imagery; and 3) sink detection from the ArcticDEM (v3). All data were compiled and filtered in a semi-automated approach, using a modified version of the MEaSUREs GIMP ice mask (https://nsidc.org/data/NSIDC-0714/versions/1) to clip the dataset to within 1 km of the ice margin. Each detected lake was then verified manually. The IIML was collected to better understand the impact of ice marginal lake change on the future sea level budget and the terrestrial and marine landscapes of Greenland, such as its ecosystems and human activities.\r\n\r\nThe IIML is a complete inventory of Greenland, with no absent data.",
    "keywords": "Ice Marginal Lakes, Greenland, Glaciers_cci, ESA",
    "publicationState": "citable",
    "dataPublishedTime": "2021-02-12T17:17:18",
    "doiPublishedTime": "2021-02-19T15:17:31",
    "updateFrequency": "notPlanned",
    "status": "completed",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/32168/?format=api",
        "dataPath": "/neodc/esacci/glaciers/data/IIML/Greenland/v1/2017/",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 88174529,
        "numberOfFiles": 10,
        "fileFormat": "vector shapefile (.shp)"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/8817/?format=api",
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2728/?format=api",
    "nonGeographicFlag": false,
    "phenomena": [],
    "dataLineage": "Andreas Wiesmann, Maurizio Santoro and Rafael Caduff (Gamma Remote Sensing) coordinated and performed the Sentinel-1 synthetic aperture radar classification workflow. Penelope How, Alexandra Messerli, Eva Mätzler, Kirsty Langley and Mikkel Høegh Bojesen (Asiaq Greenland Survey) coordinated the optical classification and sink detection workflow, and performed the post-processing, manual cleaning and compiling of the IIML. Frank Paul (University of Zurich) and Andreas Kääb (University of Oslo) advised on the dataset generation.",
    "removedDataTime": null,
    "removedDataReason": "",
    "language": "English",
    "identifier_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10803/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/10806/?format=api"
    ],
    "projects": [
        "https://api.catalogue.ceda.ac.uk/api/v2/projects/13301/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/projects/32167/?format=api"
    ],
    "observationcollection_set": [],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/142996/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/142997/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/142998/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143000/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143001/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143002/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143003/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/142999/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143004/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143005/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143006/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143007/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143008/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143009/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143010/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143011/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143012/?format=api"
    ],
    "procedureAcquisition": null,
    "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/32164/?format=api",
    "procedureComputation": null,
    "permissions": [
        {
            "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2620/?format=api",
            "useLimitation": null,
            "accessConstraints": null,
            "accessCategory": "public",
            "accessRoles": null,
            "label": "public: None group",
            "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_glaciers_terms_and_conditions.pdf",
            "licenceClassifications": "any"
        }
    ],
    "discoveryKeywords": [
        {
            "ob_id": 1138,
            "name": "NDGO0003"
        },
        {
            "ob_id": 1140,
            "name": "ESACCI"
        }
    ]
}