Survey data accompanying 'Community needs for FAIR pathogen data'

Accompanying survey results data to the mansucript 'Community needs for FAIR pathogen data', that was created under the project Pathogen Data Network project (https://pathogendatanetwork.org/; Award Number U24AI183840). Abstract Background: Datasets related to infectious diseases are essential for public health decision-making, yet their reuse remains limited by persistent barriers to data sharing and integration. Achieving data that are Findable, Accessible, Interoperable, and Reusable (FAIR) is widely recognized as essential for accelerating scientific discovery and enabling coordinated responses to emerging threats, but the needs of the global pathogen data community have not been systematically characterized. Aim: This study, conducted by the Pathogen Data Network (PDN), aims to identify infrastructural and educational priorities among stakeholders working with infectious disease-related data in order to guide community-responsive support for data sharing and interoperability. Methods: A cross-sectional stakeholder survey was disseminated to a well-defined expert population within PDN networks and via open professional channels. A total of 136 responses from researchers, healthcare professionals, bioinformaticians, and educators were analyzed descriptively to identify prioritized barriers, training needs, and preferred support mechanisms. Results: Respondents consistently identified structural constraints as the primary impediments to effective data use, including limited funding (74%), data-aggregation challenges (68%), and a shortage of skilled personnel (52%). Respondents identified bioinformatics for infectious disease research (68%) as the highest priority for training, followed by guidance on using the integrated pathogen data and tools portal provided by the PDN, the Pathogens Portal (51%). The Pathogens Portal was also ranked as the most essential PDN resource (72%). Preferred training formats included virtual short courses (68%) and webinars (66%). Notably, while researchers emphasized technical subjects like machine learning, educators prioritized foundational case studies. Conclusion: These findings provide an evidence-based diagnostic of community needs and suggest that barriers to FAIR pathogen data are predominantly systemic rather than purely technological. The survey framework and openly available dataset offer a reusable template for assessing needs in other communities and regions. By aligning training, infrastructure development, and outreach with empirically identified priorities, organizations supporting infectious disease research can strengthen the interoperability and reuse of data and establish a benchmark for future community-driven improvements.本数据集为题为《FAIR病原数据的社区需求》（*Community needs for FAIR pathogen data*）的配套调研数据集，由病原体数据网络（Pathogen Data Network, PDN）项目资助完成（项目网址：https://pathogendatanetwork.org/；资助编号：U24AI183840）。 摘要 背景：传染病相关数据集是公共卫生决策的核心支撑，但由于数据共享与整合长期存在壁垒，其复用潜力仍未充分释放。实现FAIR（可发现、可访问、可互操作、可复用，Findable, Accessible, Interoperable, and Reusable）数据已被广泛认为是加速科学发现、协调应对新兴公共卫生威胁的必要条件，但全球病原数据社区的实际需求尚未得到系统性梳理。 研究目标：本研究由病原体数据网络（Pathogen Data Network, PDN）发起，旨在明确传染病相关数据工作利益相关方的基础设施建设与教育培训优先事项，以此为导向，为数据共享与互操作提供贴合社区实际的支持方案。 研究方法：本研究采用横断面利益相关方调研设计，通过PDN内部明确界定的专家群体渠道及开放专业渠道发布调研问卷。最终回收来自科研人员、医护人员、生物信息学家及教育工作者的有效问卷共136份，通过描述性统计分析识别出优先级较高的共享壁垒、教育培训需求及偏好的支持机制。 研究结果：调研对象普遍认为，结构性限制是制约数据高效利用的核心障碍，其中包括经费不足（74%）、数据整合难题（68%）以及专业人才短缺（52%）。在教育培训优先级方面，传染病研究生物信息学（68%）位列第一，其次是关于使用PDN开发的整合型病原数据与工具门户Pathogens Portal的操作指南（51%）。Pathogens Portal同时被评为PDN最核心的资源（72%）。调研对象偏好的教育培训形式包括线上短期课程（68%）与线上研讨会（66%）。值得注意的是，科研人员更倾向于机器学习等技术类课程，而教育工作者则优先选择基础案例研究类培训。 结论：本研究结果为病原数据社区的实际需求提供了循证诊断依据，同时表明FAIR病原数据的共享壁垒主要源于系统性问题，而非单纯的技术限制。本次调研框架与公开可用的数据集，可为其他社区及区域的需求评估提供可复用的标准化模板。支持传染病研究的相关机构，若能将教育培训、基础设施建设与外联推广工作与实证识别的优先事项相契合，便可强化数据的互操作性与复用性，并为未来社区主导的优化工作树立基准。