当我们谈论大数据时,我们真正的意思是什么? 为了更精确地定义大数据
Xiaoyao Han1, Oskar Josef Gstrein1, Vasilios Andrikopoulos2
1Department of Governance and Innovation, Campus Fryslan, University of Groningen, Leeuwarden, Netherlands.
Frontiers in big data
|September 25, 2024
概括
大数据研究缺乏明确的定义,导致科学领域的各种解释. 这项研究强调了需要明确阐述大数据概念,以便更好地进行科学沟通和理解.
科学领域:
- 跨学科的科学研究.
- 信息科学 信息科学
- 计算机科学 计算机科学
背景情况:
- 大数据一词缺乏普遍接受的定义,导致科学研究的模两可.
- 现有的"V"特征并不能完全解决大数据的概念难以捉摸性.
- 在科学领域理解大数据的实际含义和各种应用方面存在差距.
研究的目的:
- 系统地审查关于大数据在科学中的使用的二级研究.
- 将大数据概念和普遍技术在不同科学领域的应用映射出来.
- 调查大数据的理论理解和实际应用之间的差异.
主要方法:
- 进行了系统性文献综述 (SLR),重点关注中学研究.
- 分析了大数据如何被理解和应用在各种科学领域.
- 将大数据的表现分类为抽象概念,大数据集,机器学习技术和大数据生态系统.
主要成果:
- 大数据技术,如机器学习和分布式计算,在各个科学领域都在使用.
- 发现了大数据表现的四大类:抽象概念,大数据集,机器学习技术和大数据生态系统.
- 研究人员对大数据表现出不同的隐含理解,尽管对"V"特征有普遍共识,但影响了研究内容.
结论:
- 大数据在科学中的理论定义和实际使用之间存在差异.
- 大数据的隐含理解显著影响研究讨论,但往往没有说明.
- 对于有效的科学沟通,更清楚地阐述大数据在研究中的意义至关重要.
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