Digital research data management is increasingly integrated across universities and research institutions, addressing the handling of research data throughout its lifecycle according to the FAIR data principles (Findable, Accessible, Interoperable, Reusable). Recent emphasis on the semantic and interlinking aspects of research data, e.g., by using ontologies and knowledge graphs further enhances findability and reusability. This work presents a framework for creating and maintaining a knowledge graph specifically for low-temperature plasma (LTP) science and technology. The framework leverages a domain-specific ontology called Plasma-O, along with the VIVO software as a platform for semantic information management in LTP research. While some research fields are already prepared to use ontologies and knowledge graphs for information management, their application in LTP research is nascent. This work aims to bridge this gap by providing a framework that not only improves research data management but also fosters community participation in building the domain-specific ontology and knowledge graph based on the published materials. The results may also support other research fields in the practical use of knowledge graphs for semantic information management.

翻译：数字研究数据管理正日益广泛地融入高校及科研机构的体系之中，其核心在于依据FAIR数据原则（可发现、可访问、可互操作、可重用）对研究数据的全生命周期进行系统化管理。近期，通过采用本体与知识图谱等技术手段强化研究数据的语义化与关联性，进一步提升了数据的可发现性与可重用性。本研究提出一个专门面向低温等离子体科学与技术领域构建与维护知识图谱的框架。该框架利用领域专用本体Plasma-O，并采用VIVO软件作为低温等离子体研究语义信息管理的平台。尽管部分研究领域已具备运用本体与知识图谱进行信息管理的基础，但此类技术在低温等离子体研究中的应用尚处于起步阶段。本工作旨在填补这一空白，提供一个不仅能改进研究数据管理、更能促进学界基于已发表材料共同参与构建领域专用本体与知识图谱的框架。该成果亦可为其他研究领域在实践中运用知识图谱实现语义信息管理提供参考。