生命科学中的数据管理工具的现状
Anna Aksenova1, Anoop Johny2, Tim Adams2
1Bonn-Aachen International Center for Information Technology (B-IT), University of Bonn, Bonn, Germany.
Frontiers in big data
|October 1, 2024
概括
有效的数据管理对于科学进步至关重要. 这项研究回顾了300多种工具和框架,这些工具和框架对于生命科学研究中的现代数据管理至关重要.
科学领域:
- 生命科学 生命科学
- 数据科学数据科学数据科学
- 信息管理 信息管理
背景情况:
- 科学研究中数据的数量和复杂性日益增加,需要强大的数据管理实践.
- 有效的数据管理对于确保数据完整性,可访问性和可用性至关重要,从而加速科学发现.
- 现代研究在重复性和创新方面严重依赖于经过良好管理的数据.
研究的目的:
- 为当代数据管理提供基本工具和框架的全面概述.
- 评估各种数据管理资源的实用性,相关性和适用性.
- 引导研究人员和机构选择适当的数据管理解决方案,特别是在生命科学领域.
主要方法:
- 对300多个数据管理工具和框架进行了系统分析.
- 评估标准包括实用性,与数据管理原则的相关性以及特定领域的适用性.
- 专注于与生命科学研究领域相关的工具.
主要成果:
- 确定支持现代数据管理的关键工具和框架.
- 评估分析资源的优点和弱点.
- 基于其功能和对研究工作流程的影响来对工具进行分类.
结论:
- 精心挑选的工具和框架可以显著提高数据管理实践.
- 这些资源的战略实施对于最大限度地提高研究效率和数据完整性至关重要.
- 这些发现为优化生命科学及其他领域的数据管理提供了实际指导.
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