Dataset Docs
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
| Field | Type | Required | Description |
|---|---|---|---|
| slug | string | Yes | Stable glossary identifier. |
| term | string | No | Preferred display label when present. |
| title | string | No | Legacy equivalent to term. |
| definition | string | Yes | Plain-language definition used in retrieval and entity pages. |
| related | string[] | No | Related vendor or technology slugs. |
| faq | object[] | No | Optional FAQ entries for grounding. |
| _meta | object | Yes | Provenance 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.