The Impact of Modern AI in Metadata Management

TL;DR

This paper explores how modern AI technologies are revolutionizing metadata management by automating processes, improving data governance, and enhancing dataset usability, through analysis, comparison, and a new AI-assisted framework.

Contribution

It introduces an innovative AI-assisted metadata management framework that automates metadata generation and addresses challenges in managing complex, modern datasets.

Findings

AI-driven methods improve metadata accuracy

Enhanced automation reduces manual effort

Framework supports better data governance

Abstract

Metadata management plays a critical role in data governance, resource discovery, and decision-making in the data-driven era. While traditional metadata approaches have primarily focused on organization, classification, and resource reuse, the integration of modern artificial intelligence (AI) technologies has significantly transformed these processes. This paper investigates both traditional and AI-driven metadata approaches by examining open-source solutions, commercial tools, and research initiatives. A comparative analysis of traditional and AI-driven metadata management methods is provided, highlighting existing challenges and their impact on next-generation datasets. The paper also presents an innovative AI-assisted metadata management framework designed to address these challenges. This framework leverages more advanced modern AI technologies to automate metadata generation, enhance governance, and improve the accessibility and usability of modern datasets. Finally, the paper outlines future directions for research and development, proposing opportunities to further advance metadata management in the context of AI-driven innovation and complex datasets.