BLbluestaq
Models and Simulations

POST /udl/aimodel

Changed on

Service operation to take a single AIModel as a POST body and ingest into the database. A specific role is required to perform this service operation. Please contact the UDL team for assistance.

Request

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

Request body

idstring

Unique identifier of the record, auto-generated by the system if not provided on create operations.

classificationMarkingstring required

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

taskstring required

Type of task this model is designed to perform.

modelVersionstring required

Version of this model.

latestTrainingDatestring date-time required

Datetime when this model was trained, in ISO 8601 UTC with millisecond precision.

descriptionstring

Description of the purpose or function of this model.

inputstring

Type of input data this model is designed to accept.

outputstring

Output or deliverable produced by this model.

modelSourcestring

Source or origin of this model.

certAuthoritiesstring[]

List of Certifying Authorities (CA) used to validate and verify performance of this model within defined operating conditions.

contentDomainstring[]

List of specific subject areas or types of content this model is designed to understand and work with.

corpusstring[]

List of the datasets used to train or evaluate this model.

latestTrainingVersionstring

Version of the most recent training dataset used by this model.

licensesstring[]

List of licenses under which this model is distributed.

limitationsstring[]

List of known limitations of this model.

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",
  "task": "Object Detection",
  "modelVersion": "1.03a",
  "latestTrainingDate": "2025-01-20T14:00:00.123Z",
  "description": "Feature extraction and identification for radar imagery",
  "input": "JPEG images",
  "output": "Heatmap",
  "modelSource": "MIT LL Radars & AI",
  "certAuthorities": [
    "DOD CA-32 17TES",
    "NIST"
  ],
  "contentDomain": [
    "Solar Panel",
    "Comms",
    "EO"
  ],
  "corpus": [
    "A-band radar imagery LEO",
    "B-band radar imagery LEO"
  ],
  "latestTrainingVersion": "2.1",
  "licenses": [
    "Apache-2.0",
    "MIT"
  ],
  "limitations": [
    "Detection performance may degrade with lower-resolution images",
    "Poor performance at night"
  ],
  "aiModelPerformance": [
    {
      "metricType": "ACCURACY",
      "metricName": "AI2 Reasoning Challenge",
      "metricDescription": "Accuracy on multiple-choice science questions",
      "resultType": "high",
      "resultValue": 0.93,
      "resultUoM": "meters"
    }
  ],
  "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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