Procedure Composite Process Instance – Django REST framework

Get a list of ProcedureComputation objects. ProcedureComputations have a 1:1 mapping with Observations where used.
These may have a number of 2 or more components made up of combinations of Computation and Acquisition records.
The details of the underlying records have been serialised.

### Available end points:

- `/ProcedureComputations/` - Will list all ProcedureComputations in the database
- `/ProcedureComputations.json` - Will return all ProcedureComputations in json format
- `/ProcedureComputations/<object_id>/` - Returns ProcedureComputations object with that id

### Available Methods:

- `GET`
- `HEAD`

### Available filters:

None
### How to use filters:

None

GET /api/v2/composites/41963/?format=api

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

{
    "ob_id": 41963,
    "computationComponent": [
        {
            "ob_id": 42315,
            "uuid": "142bd054c1544b1698077ccf8904d273",
            "title": "Computation for:  C3S: Obs4MIPs format GOME-type Total Ozone Essential Climate Variable (GTO-ECV), Version 9.0",
            "abstract": "The C3S: Obs4MIPs format GOME-type Total Ozone Essential Climate Variable (GTO-ECV), Version 9.0 dataset was generated by combining measurements from several nadir-viewing satellite sensors (GOME/ERS-2, SCIAMACHY/Envisat, OMI/Aura, GOME-2/MetOp-A, GOME-2/MetOp-B, TROPOMI/Sentinel-5P, and GOME-2/MetOp-C) into one single cohesive record.   This was done using a merging approach developed in the framework of the European Space Agency's (ESA's) Climate Change Initiative Ozone project.   Firstly, the separate pixel-based level-2 observation - produced by the GOME-type Direct FITting v4 retrieval algorithm (GODFIT) are converted into level-3 products per sensor i.e. daily and monthly averages on a regular grid of 1x1 degree in latitude and longitude.  Before the individual level-3 data records are finally merged into one single product, adjustments are applied in order  to minimize possible inter-sensor biases and/or temporal drifts. Due to its notable long-term stability one sensor (OMI/Aura) was selected to serve as a reference for the other instruments,  which are then adjusted in terms of a correction that depends on latitude and time. A detailed description of the merging approach, the generation, and the geophysical validation of GTO-ECV is provided in Coldewey-Egbers et al. (2015, 2022), Garane et al. (2018) and Lambert et al. (2022).",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        }
    ],
    "acquisitionComponent": [
        {
            "ob_id": 42314,
            "independentInstrument": [],
            "instrumentplatformpair_set": [
                {
                    "ob_id": 13964,
                    "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7813/?format=api",
                    "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2747/?format=api",
                    "relatedTo": {
                        "ob_id": 42314,
                        "uuid": "65cdb261d5714d62a1267132a797cdf2",
                        "short_code": "acq"
                    }
                },
                {
                    "ob_id": 13965,
                    "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/846/?format=api",
                    "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8029/?format=api",
                    "relatedTo": {
                        "ob_id": 42314,
                        "uuid": "65cdb261d5714d62a1267132a797cdf2",
                        "short_code": "acq"
                    }
                },
                {
                    "ob_id": 13966,
                    "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/3883/?format=api",
                    "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/4119/?format=api",
                    "relatedTo": {
                        "ob_id": 42314,
                        "uuid": "65cdb261d5714d62a1267132a797cdf2",
                        "short_code": "acq"
                    }
                },
                {
                    "ob_id": 13967,
                    "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api",
                    "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8208/?format=api",
                    "relatedTo": {
                        "ob_id": 42314,
                        "uuid": "65cdb261d5714d62a1267132a797cdf2",
                        "short_code": "acq"
                    }
                },
                {
                    "ob_id": 13968,
                    "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8299/?format=api",
                    "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8208/?format=api",
                    "relatedTo": {
                        "ob_id": 42314,
                        "uuid": "65cdb261d5714d62a1267132a797cdf2",
                        "short_code": "acq"
                    }
                },
                {
                    "ob_id": 13969,
                    "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/32134/?format=api",
                    "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8208/?format=api",
                    "relatedTo": {
                        "ob_id": 42314,
                        "uuid": "65cdb261d5714d62a1267132a797cdf2",
                        "short_code": "acq"
                    }
                }
            ]
        }
    ],
    "identifier_set": [],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/203914/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/203915/?format=api"
    ]
}