Research knowledge graphs (RKGs) have emerged as essential technology for organizing scientific knowledge, but their success depends heavily on the quality of their underlying content. Knowledge curation is a critical task to ensure the quality of (research) knowledge graphs ((R)KGs), with human curation being the gold standard despite its time- and resource-intensive nature. Automated methods, while efficient, lack the precision of human expertise. Hybrid approaches, combining automated processes with human oversight, offer a promising solution to this challenge. Dashboards can act as supportive tools in hybrid curation approaches, offering real-time updates and visual overviews. This paper presents an action research study, conducted in collaboration with the Curation and Community Building (C&CB) team of the Open Research Knowledge Graph (ORKG), to explore the development of a dashboard, called SciKGDash, designed to support knowledge curation of the ORKG. SciKGDash serves as a minimum viable product (MVP) tailored to the needs of the C&CB team, with potential for adaptation to other (R)KGs. An experiment with 15 participants demonstrated the usability of SciKGDash, with successful completion of 4 out of 5 curation tasks in under 5 minutes. In addition, SciKGDash received a positive user experience rating (UEQ score of 1.93). While the tailored solution proved effective for the ORKG, the research also highlights limitations in applying specific quality metrics across diverse (R)KGs. Future work should focus on identifying common quality metrics and enhancing SciKGDash with user-friendly features for querying customized quality metrics. Overall, knowledge curation in RKGs remains an under-explored field, warranting further research.

翻译：研究知识图谱已成为组织科学知识的关键技术，但其成功很大程度上依赖于底层内容的质量。知识策展是确保（研究）知识图谱质量的核心任务，其中人工策展虽耗费大量时间和资源，却仍是黄金标准。自动化方法虽高效，但缺乏人类专家的精确性。结合自动化流程与人工监督的混合方法为应对这一挑战提供了有前景的解决方案。仪表板可作为混合策展方法中的辅助工具，提供实时更新和可视化概览。本文介绍了一项与开放研究知识图谱策展与社区建设团队合作开展的行动研究，旨在探索开发名为SciKGDash的仪表板，以支持ORKG的知识策展。SciKGDash作为最小可行产品，专为C&CB团队需求定制，并具备适配其他（研究）知识图谱的潜力。一项包含15名参与者的实验验证了SciKGDash的可用性：5项策展任务中有4项在5分钟内成功完成。此外，SciKGDash获得了积极用户体验评分（UEQ得分1.93）。尽管该定制化方案在ORKG中表现有效，但研究也揭示了在不同（研究）知识图谱中应用特定质量指标的局限性。未来工作应聚焦于识别通用质量指标，并增强SciKGDash的易用性功能以支持自定义质量指标查询。总体而言，研究知识图谱中的知识策展仍属探索不足的领域，需进一步研究。