经过深思熟虑的数据分析
Elizabeth Bradley1, James W C White2, Joshua Garland3
1Department of Computer Science, University of Colorado-Boulder, Boulder, Colorado 80309-0430, USA and Santa Fe Institute, Santa Fe, New Mexico 87501, USA.
Chaos (Woodbury, N.Y.)
|October 30, 2024
概括
数据科学正在迅速发展,在选择正确的分析方法方面存在挑战. 这种观点主张共享原始数据,以提高科学可重复性和推进数据科学研究.
科学领域:
- 数据科学数据科学数据科学
- 科学计算科学计算
背景情况:
- 数据科学领域正在经历快速增长,这是由于数据采集,存储和处理方面的技术进步所推动的.
- 随着可用的数据数量和多样性的不断增加,科学家们面临着重大挑战.
- 除了技术进步,数据科学新方法和工具的开发也在加速.
研究的目的:
- 检查选择和应用适当的数据分析方法的挑战.
- 倡导在科学界内共享原始数据的做法.
主要方法:
- 这篇视角文章回顾了数据科学方法学的当前趋势和挑战.
- 它综合了基于数据和分析技术日益复杂的数据共享的论点.
主要成果:
- 数据科学的快速发展需要仔细考虑分析方法的选择.
- 大数据 (数量和种类) 带来的挑战是显著的.
- 建议共享原始数据是应对这些挑战的关键步骤.
结论:
- 选择正确的数据分析方法是现代数据科学中的一个关键挑战.
- 分享原始数据对于提高科学严谨性,可重复性和数据科学的进步至关重要.
- 应对数据量和多样性的挑战需要方法创新和数据共享等协作实践.
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