{
  "id": "lib-process:data-science-ml--data-collection-validation",
  "_kind": "LibraryProcess",
  "_file": "generated-library/processes.yaml",
  "_cluster": "generated-library",
  "attributes": {
    "displayName": "data-collection-validation",
    "description": "Orchestrate data ingestion from multiple sources with validation, quality checks, and versioning",
    "libraryPath": "library/specializations/data-science-ml/data-collection-validation.js",
    "specialization": "data-science-ml",
    "references": [
      "- Great Expectations: https://greatexpectations.io/\n- DVC (Data Version Control): https://dvc.org/\n- MLOps Principles: https://cloud.google.com/architecture/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning"
    ],
    "example": "const result = await orchestrate('data-science-ml/data-collection-validation', {\n  dataSources: [\n    { type: 'csv', path: 'data/raw/customers.csv', name: 'customers' },\n    { type: 'database', connection: 'postgres://...', query: 'SELECT * FROM orders', name: 'orders' }\n  ],\n  targetQuality: 85,\n  schemaPath: 'schemas/data_schema.json',\n  validationRules: ['no_missing_primary_keys', 'valid_email_format', 'positive_amounts'],\n  versioningEnabled: true\n});",
    "usesAgents": [
      "general-purpose"
    ]
  },
  "outgoingEdges": [
    {
      "from": "lib-process:data-science-ml--data-collection-validation",
      "to": "domain:data-science",
      "kind": "lib_applies_to_domain",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:data-science-ml--data-collection-validation",
      "to": "workflow:ml-model-lifecycle",
      "kind": "lib_implements_workflow",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:data-science-ml--data-collection-validation",
      "to": "specialization:data-science-ml",
      "kind": "lib_belongs_to_specialization",
      "attributes": {
        "weight": 0.9
      }
    }
  ],
  "incomingEdges": []
}