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Glossary dataset

Defined terms and related concepts for grounding identity-tech language and terminology.

Records
23
Format
JSONL
Schema Version
1.0.0
Last Updated
2025-11-10

Contract

Each record exposes a stable `slug` plus `_meta` provenance describing the source file, dataset name, canonical path, API path, license, and schema version. That is the main contract intended for downstream AI systems.

https://learn.idtechwire.com/datasets/glossary.jsonl
https://learn.idtechwire.com/datasets/schemas/glossary.schema.json

Usage

  • Use the raw JSONL file for bulk ingestion and fine-tuning pipelines.
  • Use the API for targeted retrieval when you already know the entity or slug.
  • License: CC BY 4.0
  • Generated from Markdown files in content/glossary.

Field guide

FieldTypeRequiredDescription
slugstringYesStable glossary identifier.
termstringNoPreferred display label when present.
titlestringNoLegacy equivalent to term.
definitionstringYesPlain-language definition used in retrieval and entity pages.
relatedstring[]NoRelated vendor or technology slugs.
faqobject[]NoOptional FAQ entries for grounding.
_metaobjectYesProvenance and contract metadata for this record.

Preview records

This is a human-friendly preview only. The raw file remains newline-delimited JSON.

{
  "slug": "abistemplate",
  "title": "Automated Biometric Identification System (ABIS)",
  "definition": "System for large-scale biometric matching and identification using algorithms and databases.",
  "related": [
    "matching"
  ],
  "createdAt": "2025-05-07T00:00:00.000Z",
  "updatedAt": "2025-05-07T00:00:00.000Z",
  "faq": [
    {
      "question": "What is an Automated Biometric Identification System (ABIS)?",
      "answer": "An ABIS is a system that automates large-scale biometric matching and identification using algorithms and centralized databases."
    },
    {
      "question": "How does ABIS improve biometric matching?",
      "answer": "ABIS leverages advanced algorithms to process and compare biometric data at scale, reducing manual verification and improving throughput."
    },
    {
      "question": "What are common applications of ABIS?",
      "answer": "Typical use cases include criminal investigations, border security, and large-scale identity verification in government programs."
    }
  ],
  "license": "CC-BY-4.0",
  "_meta": {
    "dataset": "glossary",
    "schemaVersion": "1.0.0",
    "license": "CC-BY-4.0",
    "sourceType": "markdown",
    "sourcePath": "content/glossary/abistemplate.md",
    "canonicalPath": "/glossary/abistemplate",
    "apiPath": "/api/glossary/abistemplate"
  }
}
{
  "slug": "consent",
  "title": "Consent",
  "definition": "Voluntary agreement by a person for their personal data to be used for specific purposes.",
  "related": [
    "gdpr"
  ],
  "createdAt": "2025-05-07T00:00:00.000Z",
  "updatedAt": "2025-05-07T00:00:00.000Z",
  "faq": [
    {
      "question": "What does consent mean in data privacy?",
      "answer": "Consent is a person’s voluntary and informed agreement for their personal data to be collected, processed, and used for specific purposes."
    },
    {
      "question": "Why is consent important for biometric data?",
      "answer": "Biometric data is sensitive; obtaining consent ensures compliance with privacy laws and respect for individual autonomy."
    },
    {
      "question": "How can organizations obtain valid consent?",
      "answer": "Valid consent requires clear information, unambiguous opt-in mechanisms, and allows individuals to withdraw consent at any time."
    }
  ],
  "license": "CC-BY-4.0",
  "_meta": {
    "dataset": "glossary",
    "schemaVersion": "1.0.0",
    "license": "CC-BY-4.0",
    "sourceType": "markdown",
    "sourcePath": "content/glossary/consent.md",
    "canonicalPath": "/glossary/consent",
    "apiPath": "/api/glossary/consent"
  }
}
{
  "slug": "deep-learning",
  "title": "Deep Learning",
  "definition": "Subset of machine learning using neural networks with multiple layers to model complex data representations.",
  "related": [
    "facial-recognition"
  ],
  "createdAt": "2025-05-07T00:00:00.000Z",
  "updatedAt": "2025-05-07T00:00:00.000Z",
  "faq": [
    {
      "question": "What is deep learning?",
      "answer": "Deep learning is a subset of machine learning that uses neural networks with multiple layers to model complex patterns and representations."
    },
    {
      "question": "How is deep learning used in biometric systems?",
      "answer": "Techniques like convolutional neural networks (CNNs) extract high-dimensional features from biometric data (e.g., face, fingerprint) to improve recognition accuracy."
    },
    {
      "question": "Why is deep learning important for biometric matching?",
      "answer": "Deep learning models automatically learn discriminative features, reducing manual feature engineering and enhancing performance across varied conditions."
    }
  ],
  "license": "CC-BY-4.0",
  "_meta": {
    "dataset": "glossary",
    "schemaVersion": "1.0.0",
    "license": "CC-BY-4.0",
    "sourceType": "markdown",
    "sourcePath": "content/glossary/deep-learning.md",
    "canonicalPath": "/glossary/deep-learning",
    "apiPath": "/api/glossary/deep-learning"
  }
}

What the preview shows

The first preview record demonstrates the stable entity fields plus the `_meta` provenance block. Downstream systems should treat `_meta.schemaVersion` as the contract version and `_meta.sourcePath` as the origin indicator.