Making data and metadata FAIR (Findable, Accessible, Interoperable, Reusable) has become an important objective in research and industry, and knowledge graphs and ontologies have been cornerstones in many going-FAIR strategies. In this process, however, human-actionability of data and metadata has been lost sight of. Here, in the first part, I discuss two issues exemplifying the lack of human-actionability in knowledge graphs and I suggest adding the Principle of human Explorability to extend FAIR to the FAIREr Guiding Principles. Moreover, in its interoperability framework and as part of its GoingFAIR strategy, the European Open Science Cloud initiative distinguishes between technical, semantic, organizational, and legal interoperability and I argue to add cognitive interoperability. In the second part, I provide a short introduction to semantic units and discuss how they increase the human explorability and cognitive interoperability of knowledge graphs. Semantic units structure a knowledge graph into identifiable and semantically meaningful subgraphs, each represented with its own resource that instantiates a corresponding semantic unit class. Three categories of semantic units can be distinguished: Statement units model individual propositions, compound units are semantically meaningful collections of semantic units, and question units model questions that translate into queries. I conclude with discussing how semantic units provide a framework for the development of innovative user interfaces that support exploring and accessing information in the graph by reducing its complexity to what currently interests the user, thereby significantly increasing the cognitive interoperability and thus human-actionability of knowledge graphs.

翻译：使数据及元数据遵循FAIR（可发现、可访问、可互操作、可复用）原则已成为研究界和工业界的重要目标，而知识图谱与本体论在许多推进FAIR的策略中扮演着基石角色。然而在这一过程中，数据及元数据的人类可操作性却被忽视了。本文第一部分讨论了知识图谱中体现人类可操作性缺失的两个问题，并提出增加"人类可探索性"原则，将FAIR扩展为FAIREr指导原则。此外，欧洲开放科学云倡议在其互操作性框架及实现FAIR策略中，区分了技术、语义、组织与法律互操作性，我主张应增加认知互操作性。第二部分简要介绍了语义单元，并探讨其如何提升知识图谱的人类可探索性与认知互操作性。语义单元将知识图谱结构化为可识别且具有语义意义的子图，每个子图由其实例化对应语义单元类的独立资源表示。可区分三类语义单元：陈述单元建模单个命题，复合单元是语义上有意义的语义单元集合，问题单元建模可转化为查询的问题。最后，我讨论了语义单元如何为开发创新用户界面提供框架——通过将图谱复杂性简化为用户当前关注的信息，支持用户探索和获取图谱中的信息，从而显著提升知识图谱的认知互操作性及人类可操作性。