BLbluestaq
Models and Simulations

POST /udl/aiprediction/createBulk

Changed on

Service operation intended for initial integration only, to take a list of AIPrediction records as a POST body and ingest into the database. This operation is not intended to be used for automated feeds into UDL. Data providers should contact the UDL team for specific role assignments and for instructions on setting up a permanent feed through an alternate mechanism.

Request

  • Base URL
    https://unifieddatalibrary.com
  • URL
    https://unifieddatalibrary.com/udl/aiprediction/createBulk
  • Auth
    none declared

Request body

idstring

Unique identifier of the record, auto-generated by the system.

classificationMarkingstring required

Classification marking of the data in IC/CAPCO Portion-marked format.

idAIModelstring required

Unique identifier of the model associated with the prediction.

predictionIdstring required

Unique identifier for this prediction. This may be an internal identifier and not necessarily map to a valid identifier within the UDL.

predictionTimestring date-time required

Datetime this prediction was made, in ISO 8601 UTC with millisecond precision.

predictionSourcestring

Source or origin of this prediction.

prePipelineVersionstring

Version of the preprocessing pipeline used prior to this prediction. The pipeline is the structured sequence of steps applied to the input data to convert it to a standardized format.

rtestring[]

List of runtime environment components used for this prediction, such as hardware, operating system, etc.

batchSizeinteger

Number of input items processed together in a single inference batch.

latencynumber double

Total time taken to complete the prediction request in milliseconds.

tagsstring[]

Optional array of provider/source specific tags for this data, where each element is no longer than 32 characters, used for implementing data owner conditional access controls to restrict access to the data. Should be left null by data providers unless conditional access controls are coordinated with the UDL team.

transactionIdstring

Optional identifier to track a commercial or marketplace transaction executed to produce this data.

createdAtstring date-time

Time the row was created in the database, auto-populated by the system.

createdBystring

Application user who created the row in the database, auto-populated by the system.

updatedAtstring date-time

Time the row was last updated in the database, auto-populated by the system.

updatedBystring

Application user who updated the row in the database, auto-populated by the system.

sourceDLstring

The source data library from which this record was received. This could be a remote or tactical UDL or another data library. If null, the record should be assumed to have originated from the primary Enterprise UDL.

sourcestring required

Source of the data.

originstring

Originating system or organization which produced the data, if different from the source. The origin may be different than the source if the source was a mediating system which forwarded the data on behalf of the origin system. If null, the source may be assumed to be the origin.

origNetworkstring

The originating source network on which this record was created, auto-populated by the system.

dataMode'REAL' | 'TEST' | 'SIMULATED' | 'EXERCISE' required

Indicator of whether the data is REAL, TEST, EXERCISE, or SIMULATED data:

REAL: Data collected or produced that pertains to real-world objects, events, and analysis.

TEST: Specific datasets used to evaluate compliance with specifications and requirements, and for validating technical, functional, and performance characteristics.

EXERCISE: Data pertaining to a government or military exercise. The data may include both real and simulated data.

SIMULATED: Synthetic data generated by a model to mimic real-world datasets.

Example request

[
  {
    "id": "026dd511-8ba5-47d3-9909-836149f87686",
    "classificationMarking": "U",
    "idAIModel": "341c5509-80c3-4298-9d78-32f818313af5",
    "predictionId": "run-20250808",
    "predictionTime": "2025-01-01T16:00:00.123Z",
    "predictionSource": "MIT LL SSN testbed",
    "prePipelineVersion": "v2.1.0",
    "rte": [
      "NVIDIA A100",
      "Ubuntu 22.04"
    ],
    "batchSize": 32,
    "latency": 47.5,
    "aiPredictionReviews": [
      {
        "status": "IN REVIEW",
        "reviewer": "John Doe",
        "reviewDate": "2025-01-02T16:00:00.123Z",
        "corrections": [
          "Added car",
          "Adjusted bicycle to motorcycle"
        ],
        "notes": "Example notes"
      }
    ],
    "aiPredictionEntities": [
      {
        "entitySourceType": "Radar sensor",
        "entitySourceId": "SSN1",
        "entitySourceName": "Big SSN Radar",
        "entitySourceDetails": "Primary",
        "entityType": "IMAGE",
        "entityId": "image123",
        "entityRole": "INPUT",
        "entityURI": "Example URI",
        "mimeType": "IMAGE/PNG",
        "checksumAlgorithm": "SHA-256",
        "checksumValue": "abc123"
      }
    ],
    "aiPredictionAssociations": [
      {
        "assocEntityId": "image123",
        "assocData": "IMAGE",
        "assocType": "EXPLANATION",
        "assocContext": "Explanation generated using SHAP values",
        "assocDataKeys": [
          "Base Value",
          "Output Value"
        ],
        "assocDataValues": [
          0.5,
          0.67
        ],
        "assocDataUofMs": [
          "meters",
          "meters"
        ],
        "assocTimestamp": "2025-01-01T17:00:00.123Z"
      }
    ],
    "aiPredictionContents": [
      {
        "contentOutput": "Image identified as a Solar Panel",
        "contentType": "LABEL",
        "confidenceScore": 0.77,
        "aiPredictionContentExplanations": [
          {
            "explanationType": "ACTIVATION MAP",
            "explanationFormat": "IMAGE",
            "aiPredictionContentExplanationData": [
              {
                "elementType": "FEATURE",
                "elementName": "SIZE",
                "elementValue": 0.3,
                "elementUofM": "meters",
                "impactScore": 80.1,
                "explanationDataNotes": "Example notes"
              }
            ]
          }
        ],
        "aiPredictionContentUncertainties": [
          {
            "uncertCategory": "EPISTEMIC",
            "uncertType": "STANDARD DEVIATION",
            "uncertDescription": "Amount of variability of solar array performance metrics.",
            "uncertMethod": "ENSEMBLE",
            "confidenceLevel": 95,
            "lowerBound": 0.23,
            "upperBound": 0.87,
            "ensembleMethod": "BAGGING",
            "ensembleSize": 5,
            "samplingMethod": "MONTE CARLO",
            "samplingCount": 100,
            "seeds": [
              42,
              100,
              2024,
              8,
              7
            ],
            "calibrationTechnique": "TEMPERATURE SCALING",
            "calibrationParameter": "Temperature",
            "ece": 0.021,
            "brierScore": 0.12,
            "nll": 1.74,
            "uncertKeys": [
              "Power",
              "Efficiency",
              "Temperature"
            ],
            "uncertValues": [
              12.5,
              0.03,
              1.8
            ],
            "uncertUofMs": [
              "Watts",
              "Percent",
              "degC"
            ],
            "uncertNotes": "Example notes"
          }
        ]
      }
    ],
    "tags": [
      "TAG1",
      "TAG2"
    ],
    "transactionId": "TRANSACTION-ID",
    "createdAt": "2018-01-01T16:00:00.123Z",
    "createdBy": "some.user",
    "updatedAt": "2018-01-01T16:00:00.123Z",
    "updatedBy": "some.user",
    "sourceDL": "AXE",
    "source": "Bluestaq",
    "origin": "THIRD_PARTY_DATASOURCE",
    "origNetwork": "OPS1",
    "dataMode": "TEST"
  }
]

Response

Success

Changes

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