用AI自动管理元数据，提升数据可用性与治理效率。
The Impact of Modern AI in Metadata Management
- 结合AI技术自动化生成和管理元数据。
- 框架显著提升现代数据集的可访问性与易用性。
- 适合数据治理与AI研发团队参考。
元数据管理在数据驱动时代对数据治理、资源发现和决策至关重要。传统方法侧重于组织、分类和资源复用，而现代人工智能（AI）技术的融入已深刻改变这一流程。本文通过分析开源方案、商业工具和研究项目，对比了传统与AI驱动的元数据管理方法，揭示现有挑战及其对下一代数据集的影响。论文提出一种创新的AI辅助元数据管理框架，利用先进AI技术实现元数据自动生成、增强治理，并提升现代数据集的可访问性与可用性。最后，展望未来研究方向，提出在AI驱动创新与复杂数据背景下进一步推进元数据管理的机遇。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。