弥合科学知识差距和可重复性:来源,断言和证据本体学的调查
Tek Raj Chhetri1, Yaroslav O Halchenko2, Dorota Jarecka1
1McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
概括
科学本体和知识图 (KG) 结构数据以提高可重复性. 这篇评论考察了23个断言,证据和来源的本体学,确定了科学进步的挑战和机会.
科学领域:
- 生物医学信息学
- 数据科学
- 科学出版
背景情况:
- 科学出版物和复杂的实验设计的快速增长使其难以保持最新状态.
- 不结构化的科学断言和有限的来源阻碍了研究的可复制性.
- 需要结构化数据表示以捕捉断言,证据和来源.
研究的目的:
- 审查现有的本体论,以捕捉科学断言,证据和来源.
- 提供有关本体论的现状概述.
- 确定这一领域的主要挑战和机遇.
主要方法:
- 科学文献的系统审查.
- 识别和分析了23个本体.
- 本体论的分类是以断言/证据 (13) 和来源 (10) 为重点的.
主要成果:
- 一个23个本体的景观被识别和分析.
- 13个本体论集中在断言和证据上.
- 十个本体学聚焦在来源上.
结论:
- 实体学和知识图 (KG) 对于科学数据的结构至关重要.
- 解决当前存在的挑战可以提高可重现性.
- 需要进一步发展以充分利用知识产权促进科学进步.
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