The Impact of Modern AI in Metadata Management
arXiv:2501.16605 · doi:10.1007/s44230-025-00106-5
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.
References in corpus (16)
- HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face
- Data Mesh: a Systematic Gray Literature Review
- KubeEdge.AI: AI Platform for Edge Devices
- From Text to Insight: Large Language Models for Materials Science Data Extraction
- AI-Driven Frameworks for Enhancing Data Quality in Big Data Ecosystems: Error_Detection, Correction, and Metadata Integration
- Participatory Approaches in AI Development and Governance: A Principled Approach
- Metadata Integration for Spam Reviews Detection on Vietnamese E-commerce Websites
- A Standardized Machine-readable Dataset Documentation Format for Responsible AI
- AgentSquare: Automatic LLM Agent Search in Modular Design Space
- A Generative AI-driven Metadata Modelling Approach
- TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems
- TapeAgents: a Holistic Framework for Agent Development and Optimization
- Brame: Hierarchical Data Management Framework for Cloud-Edge-Device Collaboration
- Ontology-supported AI Model and Dataset Management
- metabench -- A Sparse Benchmark of Reasoning and Knowledge in Large Language Models
- Leveraging Retrieval Augmented Generative LLMs For Automated Metadata Description Generation to Enhance Data Catalogs