The Zenith Law Glossary is your guide through evolving cross-domain terminology, including but not limited to engineering, governance, legal, policy, and AI topics, providing concise definitions and context for further exploration. Each term is linked to a source and related article for deeper reference and applied context. Glossary terms are grouped A-Z and mapped to related site articles. Each definition includes a source link so the page is useful for readers, search engines, and answer systems that need concise, attributable definitions.

This glossary is informational and educational. It is not legal advice, and legal obligations can vary by jurisdiction.

Source tiers distinguish authority level: external standards and peer-reviewed sources are shown separately from internal editorial synthesis links.

Source tier guide: Tier 1 = official standards or peer-reviewed primary sources; Tier 3 = reference encyclopaedias and general technical references; Internal synthesis (editorial) = this site's own evidence-grounded summaries.

Tier 3 references support orientation and discovery. They should not be treated as authoritative legal advice or as a substitute for jurisdiction-specific primary legal sources.

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

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Data Lineage

Data lineage records how data moves and transforms across systems, while preserving dependency paths from source to downstream outputs.

Source: Data lineage (Tier 3 (reference encyclopaedia))

Related: Data Provenance in Machine Learning

Digital Sovereignty

In this glossary context, digital sovereignty describes jurisdiction-level control expectations for data handling, cloud operations, and digital infrastructure governance boundaries.

Source: Digital Sovereignty in Practice (Internal synthesis (editorial))

Related: Digital Sovereignty in Practice

F

Federated Learning

Federated learning trains a shared model across distributed nodes without centralising raw data, reducing direct data-movement exposure.

Source: Federated learning (Tier 3 (reference encyclopaedia))

Related: Large Language Models in Practice

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Graph Neural Network

A graph neural network is a model family that learns from node-edge structures, making it useful for relational provenance and dependency analysis.

Source: Graph neural network (Tier 3 (reference encyclopaedia))

Related: Data Provenance in Machine Learning

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Knowledge Distillation

Knowledge distillation transfers behavior from a larger teacher model to a smaller student model to improve efficiency while retaining useful performance.

Source: Knowledge distillation (Tier 3 (reference encyclopaedia))

Related: Large Language Models in Practice

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Prompt Engineering

Prompt engineering is the disciplined design and testing of model instructions to improve accuracy, consistency, and controllability.

Source: Prompt engineering (Tier 3 (reference encyclopaedia))

Related: Large Language Models in Practice

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Frequently Asked Questions

What is this glossary for?

This page provides quick definitions for recurring terms across engineering, governance, legal, policy, and AI topics published across the site.

How should I use these definitions?

Start with the one-line definition, then open the source link for a deeper reference and the related post link for applied context from this site.

Why are source links included on each card?

Source links make each definition attributable and easier for readers and AI retrieval systems to validate before reuse.

What is the difference between SEO, GEO, and AEO in this context?

SEO improves discoverability in search results, GEO may improve citation likelihood in generative AI responses, and AEO improves extraction quality for direct-answer systems.