对数据抽象的审查
Gianluca Cima1, Marco Console1, Maurizio Lenzerini1
1Dipartimento di Ingegneria Informatica, Automatica e Gestionale "A. Ruberti", Sapienza University of Rome, Rome, Italy.
Frontiers in artificial intelligence
|July 10, 2023
概括
数据抽象对于有效的人工智能 (AI) 和机器学习 (ML) 是至关重要的,通过确保数据是可查找,可访问,可互操作和可重复使用 (FAIR). 本综述探讨了数据抽象的方法.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 数据管理数据管理
背景情况:
- 有效的人工智能 (AI) 和机器学习 (ML) 在很大程度上取决于强大的数据准备.
- 现代数据通常存在于分布式和异质来源中,使数据收集复杂化.
- 对数据服务来说,FAIR指导原则 (可查找,可访问,可互操作,可重复使用) 是必不可少的.
研究的目的:
- 审查有关数据抽象技术的现有研究.
- 为定义数据抽象提供一个正式的框架.
- 讨论数据抽象问题的决定性和复杂性,并概述未来的研究方向.
主要方法:
- 审查数据抽象的理论框架.
- 分析数据抽象中的核心问题的可决性和复杂性.
- 综合当前的研究成果,并确定未解决的问题.
主要成果:
- 数据抽象通过反向工程提供数据服务的语义特征.
- 已经开发了用于数据抽象的正式框架.
- 报告了关键抽象问题的决定性和复杂性结果.
结论:
- 数据抽象是解决分布式数据集成挑战的重要技术.
- 数据抽象的正式化有助于使数据服务符合FAIR标准.
- 需要进一步的研究来推进数据抽象的方法和应用.
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