A plethora of scholarly knowledge is being published on distributed scholarly infrastructures. Querying a single infrastructure is no longer sufficient for researchers to satisfy information needs. We present a GraphQL-based federated query service for executing distributed queries on numerous, heterogeneous scholarly infrastructures (currently, ORKG, DataCite and GeoNames), thus enabling the integrated retrieval of scholarly content from these infrastructures. Furthermore, we present the methods that enable cross-walks between artefact metadata and artefact content across scholarly infrastructures, specifically DOI-based persistent identification of ORKG artefacts (e.g., ORKG comparisons) and linking ORKG content to third-party semantic resources (e.g., taxonomies, thesauri, ontologies). This type of linking increases interoperability, facilitates the reuse of scholarly knowledge, and enables finding machine actionable scholarly knowledge published by ORKG in global scholarly infrastructures. In summary, we suggest applying the established linked data principles to scholarly knowledge to improve its findability, interoperability, and ultimately reusability, i.e., improve scholarly knowledge FAIR-ness.

中文翻译：

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使用 GraphQL 联合学术基础设施

大量的学术知识正在分布式学术基础设施上发表。查询单个基础设施已不足以满足研究人员的信息需求。我们提出了一种基于 GraphQL 的联合查询服务，用于在众多异构学术基础设施（目前，ORKG、DataCite 和 GeoNames）上执行分布式查询，从而能够从这些基础设施中集成检索学术内容。此外，我们提出了跨学术基础设施实现人工制品元数据和人工制品内容之间交叉的方法，特别是基于 DOI 的 ORKG 人工制品的持久识别（例如，ORKG 比较）并将 ORKG 内容链接到第三方语义资源（例如，分类法） 、叙词表、本体）。这种类型的链接增加了互操作性，促进学术知识的重用，并能够在全球学术基础设施中查找由 ORKG 发布的机器可操作的学术知识。总之，我们建议将已建立的关联数据原则应用于学术知识，以提高其可查找性、互操作性和最终的可重用性，即提高学术知识的公平性。