发表机构
FIZ Karlsruhe（德国卡尔斯鲁厄信息中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出涵盖250年数学学术成果的zbMATH开放知识图谱，整合专家语义内容，含3400万实体及1.68亿三元组，可支持细粒度数学学术关系分析，为数学知识研究提供开放语义基础设施。
AI 中文摘要
我们提出了 zbMATH 开放知识图谱（KG），这是一个涵盖超过 250 年数学学术成果的大规模 RDF 知识图谱。与现有主要捕获文献元数据和引用结构的学术知识图谱不同，zbMATH 开放 KG 整合了专家精心整理的语义内容，包括评论、关键词、学科分类、软件引用以及消歧后的作者身份。这种数学知识的领域特定表示与广泛时间覆盖的结合，支持对数学概念、研究领域和随时间变化的学术关系进行细粒度探索所需的分析。最终的图谱包含 3400 万个实体和 1.68 亿个 RDF 三元组，采用成熟的语义网词汇表表示，支持互操作性和 FAIR 数据原则。我们还通过查询驱动的、基于历史的学术探索用例展示了其能力，说明该知识图谱如何呈现仅从文献和引用信息中可能难以识别的关系和模式。zbMATH 开放 KG 为研究数学知识的发展以及追踪数百年学术成果间的联系提供了开放的语义基础设施。
英文摘要
We present the zbMATH Open Knowledge Graph, a large-scale RDF knowledge graph (KG) covering more than 250 years of mathematical scholarship. Unlike existing scholarly knowledge graphs that primarily capture bibliographic metadata and citation structures, the zbMATH Open KG integrates expert-curated semantic content, including reviews, keywords, subject classifications, software references, and disambiguated authorship. This combination of domain-specific representation of mathematical knowledge and extensive temporal coverage supports analyses that require fine-grained exploration of mathematical concepts, research fields, and scholarly relationships over time. The resulting graph comprises 34 million entities and 168 million RDF triples represented using established Semantic Web vocabularies, supporting interoperability and FAIR data principles. We further demonstrate its capabilities through query-driven historically grounded scholarly exploration use cases, illustrating how the knowledge graph can surface relationships and patterns that may be difficult to identify from bibliographic and citation information alone. The zbMATH Open KG provides an open semantic infrastructure for studying the development of mathematical knowledge and tracing scholarly connections across centuries of scholarship.
