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The Impact of Modern AI in Metadata Management

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arxiv 2501.16605 v2 pith:KEDTWVWP submitted 2025-01-28 cs.DB cs.AI

The Impact of Modern AI in Metadata Management

classification cs.DB cs.AI
keywords metadatamanagementmodernai-drivendatasetstraditionalapproacheschallenges
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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