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Ontologies and languages for representing mathematical knowledge on the Semantic Web

机译:用于在语义网上表示数学知识的本体和语言

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摘要

Mathematics is a ubiquitous foundation of science, technology, and engineering. Specific areas of mathematics, such as numeric and symbolic computation or logics, enjoy considerable software support. Working mathematicians have recently started to adopt Web 2.0 environments, such as blogs and wikis, but these systems lack machine support for knowledge organization and reuse, and they are disconnected from tools such as computer algebra systems or interactive proof assistants. We argue that such scenarios will benefit from Semantic Web technology. Conversely, mathematics is still underrepresented on the Web of [Linked] Data. There are mathematics-relaated Linked Data, for example statistical government data or scientific publication databases, but their mathematical semantics has not yet been modeled. We argue that the services for the Web of Data will benefit from a deeper representation of mathematical knowledge. Mathematical knowledge comprises structures given in a logical language - formulae, statements (e.g. axioms), and theories -, a mixture of rigorous natural language and symbolic notation in documents, application-specific metadata, and discussions about conceptualizations, formalizations, proofs, and (counter-)examples. Our review of vocabularies for representing these structures covers ontologies for mathematical problems, proofs, interlinked scientific publications, scientific discourse, as well as mathematical metadata vocabularies and domain knowledge from pure and applied mathematics. Many fields of mathematics have not yet been implemented as proper Semantic Web ontologies; however, we show that MathML and OpenMath, the standard XML-based exchange languages for mathematical knowledge, can be fully integrated with RDF representations in order to contribute existing mathematical knowledge to the Web of Data. We conclude with a roadmap for getting the mathematical Web of Data started: what datasets to publish, how to interlink them, and how to take advantage of these new connections.
机译:数学是科学,技术和工程的普遍基础。数学的特定领域(例如数字和符号计算或逻辑)享有相当多的软件支持。工作的数学家最近开始采用Web 2.0环境,例如博客和Wiki,但是这些系统缺乏对知识组织和重用的机器支持,并且与诸如计算机代数系统或交互式证明助手之类的工具断开连接。我们认为,这种情况将从语义Web技术中受益。相反,在[Linked]数据网上,数学仍然没有得到很好的体现。存在与数学相关的链接数据,例如政府统计数据或科学出版物数据库,但尚未对其数学语义建模。我们认为,Web数据服务将受益于更深入的数学知识表示。数学知识包括以逻辑语言给出的结构-公式,陈述(例如公理)和理论-严格的自然语言和文档中的符号表示法,特定于应用程序的元数据以及关于概念化,形式化,证明和(反例)。我们对代表这些结构的词汇的综述涵盖了数学问题的本体论,证明,相互关联的科学出版物,科学话语,以及数学元数据词汇和来自纯数学和应用数学的领域知识。许多数学领域尚未实现为适当的语义网本体。但是,我们展示了MathML和OpenMath(用于数学知识的基于XML的标准交换语言)可以与RDF表示形式完全集成,以便将现有的数学知识贡献给Web数据。我们以开始建立数学数据网络的路线图作为结束:发布哪些数据集,如何相互链接以及如何利用这些新连接。

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