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科学领域:

  • 材料科学 材料科学 材料科学
  • 数据科学数据科学数据科学
  • 计算科学 计算科学

背景情况:

  • 公平的数据原则 (可查找性,可访问性,互操作性,可重复使用性) 对于推进数据驱动的材料科学至关重要.
  • 现有的软件解决方案用于实施FAIR原则,特别是用于标准化异质数据和实现数据访问,是有限的.
  • 材料数据的高效利用和重复使用受到数据标准化和访问方面的挑战的阻碍.

研究的目的:

  • 引入一个新的材料数据公平化框架 (FFMDFPA),以克服当前在材料数据公平化方面的局限性.
  • 为处理来自各种来源的原始半结构化数据提供无代码,灵活的解决方案.
  • 通过标准化的API来促进无的数据共享和重复使用.

主要方法:

  • 开发一个材料数据的 FAIRification 框架 (FFMDFPA),其中包含一个无代码,基于模板的解析器.
  • 实现一个灵活的,半结构化的解析器,用于从各种文本格式中提取和转换数据,而不需要编码.
  • 设计一个具有高效查询语法的标准化API,以简化数据访问和共享.

主要成果:

  • 使用基于模板的解析器,FFMDFPA成功地从各种文本格式中提取和转换半结构化数据.
  • 该框架提供了无需编码的数据操纵灵活性,提高了可用性.
  • 一个标准化的API促进了有效的数据查询和材料数据的无共享.

结论:

  • FFMDFPA为材料科学中的FAIR数据实现提供了一个实际的解决方案,解决了适当软件的稀缺问题.
  • 该框架的无代码解析器和标准化的API促进了材料数据的高效利用和重复使用.
  • 在FFMDFPA中的数据语义操纵技术对材料科学之外的文本数据的 FAIRification 有更广泛的含义.