Vogt Lars, Strömert Philip, Matentzoglu Nicolas, Karam Naouel, Konrad Marcel, Prinz Manuel, Baum Roman
TIB Leibniz Information Centre for Science and Technology, Welfengarten 1B, 30167, Hanover, Germany.
NICO: Semanticly, Athens, Greece.
Sci Data. 2025 Apr 24;12(1):688. doi: 10.1038/s41597-025-05011-x.
FAIR (meta)data presuppose their successful communication between machines and humans while preserving meaning and reference. The FAIR Guiding Principles lack specificity regarding semantic interoperability. We adopt a linguistic perspective on semantic interoperability and investigate the structures and conventions ensuring reliable communication of textual information, drawing parallels with data structures by understanding both as models. We propose a conceptual model of semantic interoperability, comprising intensional and extensional terminological interoperability, as well as logical and schema propositional interoperability. Since there cannot be a universally accepted best vocabulary and best (meta)data schema, establishing semantic interoperability necessitates the provision of comprehensive sets of intensional and extensional entity mappings and schema crosswalks. In accordance with our conceptual model, we suggest additions to the FAIR Guiding Principles that encompass the requirements for semantic interoperability. Additionally, we argue that attaining FAIRness of (meta)data requires not only their organization into FAIR Digital Objects, but also the establishment of a FAIR ecosystem of FAIR Services, that include a terminology, a schema, and an operations service.
FAIR(元)数据预先假定它们在机器和人类之间成功通信,同时保留意义和指代。FAIR指导原则在语义互操作性方面缺乏具体性。我们从语言角度看待语义互操作性,并研究确保文本信息可靠通信的结构和惯例,通过将两者都理解为模型来与数据结构进行类比。我们提出了一个语义互操作性的概念模型,包括内涵和外延术语互操作性,以及逻辑和模式命题互操作性。由于不可能有一个普遍接受的最佳词汇表和最佳(元)数据模式,建立语义互操作性需要提供全面的内涵和外延实体映射集以及模式交叉引用。根据我们的概念模型,我们建议对FAIR指导原则进行补充,以涵盖语义互操作性的要求。此外,我们认为实现(元)数据的FAIRness不仅需要将它们组织成FAIR数字对象,还需要建立一个包括术语、模式和操作服务的FAIR服务的FAIR生态系统。