用形式语义表达高级科学声明
Expressing High-Level Scientific Claims with Formal Semantics
摘要：
语义技术的使用在科学传播中获得了巨大的吸引力，在生命科学、计算机科学和社会科学等学科中有着广泛的应用。像RDF、OWL和其他基于形式逻辑的形式主义语言被应用于使科学知识不仅对人类读者而且对自动化系统都是可访问的。这些方法主要侧重于科学出版物本身的结构，所使用的科学方法和设备，或所使用的数据集的结构。科学工作的核心主张或假设只是以一种肤浅的方式被涵盖，例如将所提到的实体与既定的标识符联系起来。因此，在这项研究中，我们想找出我们是否可以使用现有的语义形式主义，充分表达的内容，高层次的科学主张，使用形式语义系统的方式。从所有学科的科学文章的样本分析的主要索赔，我们发现，他们的语义比什么是直接的应用程序的形式化，如RDF或OWL帐户更复杂，但我们设法引出一个明确的语义模式，我们称之为“超级模式”。我们在这里展示了这个超模式的五个槽的实例化如何导致高阶逻辑中严格定义的语句。我们成功地将这种超级模式应用于科学声明的扩大样本。我们发现，知识表示专家，指示独立实例化的超级模式与给定的科学索赔，表现出高度的一致性和收敛性的任务和主题的复杂性。因此，这些结果为以一种可以自动解释的方式表达高水平的科学发现打开了大门，从长远来看，这可以让我们进行自动一致性检查，等等。
英文摘要：
The use of semantic technologies is gaining significant traction in science communication with a wide array of applications in disciplines including the Life Sciences, Computer Science, and the Social Sciences. Languages like RDF, OWL, and other formalisms based on formal logic are applied to make scientific knowledge accessible not only to human readers but also to automated systems. These approaches have mostly focused on the structure of scientific publications themselves, on the used scientific methods and equipment, or on the structure of the used datasets. The core claims or hypotheses of scientific work have only been covered in a shallow manner, such as by linking mentioned entities to established identifiers. In this research, we therefore want to find out whether we can use existing semantic formalisms to fully express the content of high-level scientific claims using formal semantics in a systematic way. Analyzing the main claims from a sample of scientific articles from all disciplines, we find that their semantics are more complex than what a straight-forward application of formalisms like RDF or OWL account for, but we managed to elicit a clear semantic pattern which we call the 'super-pattern'. We show here how the instantiation of the five slots of this super-pattern leads to a strictly defined statement in higher-order logic. We successfully applied this super-pattern to an enlarged sample of scientific claims. We show that knowledge representation experts, when instructed to independently instantiate the super-pattern with given scientific claims, show a high degree of consistency and convergence given the complexity of the task and the subject. These results therefore open the door for expressing high-level scientific findings in a manner they can be automatically interpreted, which on the longer run can allow us to do automated consistency checking, and much more.
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