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Introduction

1. Introduction

AI for Metadata Quality

2. Generative AI for Metadata Quality
3. Metadata Quality Assessment with LLM

Metadata Augmentation

4. Metadata Augmentation Methodology
5. Metadata Augmentation: Technical Details

Data Discoverability

6. Data Discoverability

Model Context Protocol (MCP) for AI-centric Data Dissemination

7. Model Context Protocol (MCP) for AI-centric Data Dissemination

Monitoring of Data Use

8. Monitoring of Data Use

Anomaly Detection in Data

9. Anomaly Detection in Development Data
10. Anomaly Explanation Methodology Handbook
11. Motivation: Why LLM Elicitation for Anomaly Explanation
12. Elicitation Pipeline: How It Works
13. Reviewer Feedback System
14. Timeseries Anomaly Explanation with LLMs

Efficient and Inclusive AI Applications

15. Efficient and Inclusive AI Applications

Partnerships

16. Partnerships

Repository
Open issue

Index

By Development Data Group

Last updated on Mar 24, 2026.

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