发表机构
Leibniz Institute of Vegetable and Ornamental Crops (IGZ); TIB - Leibniz Information Centre for Science and Technology; Humboldt-Universität zu Berlin; International Security and Development Center (ISDC)（莱布尼茨蔬菜与观赏作物研究所; 莱布尼茨科学与技术信息中心; 柏林洪堡大学; 国际安全与发展中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出一个连接基于文献与基础设施支持的知识整合框架，通过37项研究的案例发现，仅8%的数据可重用，并利用TIB知识织机实现直接综合，强调知识整合需依赖可访问、可执行和可重用的数据与工作流程。
AI 中文摘要
跨学科知识整合是可持续性研究的核心，然而大多数证据综合方法依赖于出版物中报告的研究结果，限制了对底层数据和工作流程的验证与重用。我们开发了一个概念框架，将基于文献的知识整合与基础设施支持的知识整合联系起来，并通过一项系统性综述案例研究来考察整合何时能够超越已报告的研究结果。我们回顾了37项关于气候变化、暴力冲突和家庭粮食安全的研究。基于文献的综合能够对所有纳入的研究进行整合，而可重用输出的获取则有限：超过一半的研究未提供数据可用性声明，27%报告可按需提供，但仅有8%提供了可重用的数据和工作流程。为探索基础设施支持的综合，我们使用TIB知识织机将具有可访问数据和代码的研究表示为机器可读输出，并从手动提取和织机衍生的数据中生成知识缺口图（KGM），比较手动综合与基础设施支持的综合。在输出可重用的情况下，综合可以直接从数据和工作流程而非出版物中生成。这些发现表明，基于文献的综合可以通过基础设施支持的综合得到补充，前提是输出可访问且可用，并且推进知识整合不仅依赖于基础设施，还取决于使数据、代码和工作流程可访问、可执行和可重用。
英文摘要
Integrating knowledge across disciplines is central to sustainability research, yet most evidence-synthesis methods rely on findings as reported in publications, limiting verification and reuse of underlying data and workflows. We develop a conceptual framework linking literature-based and infrastructure-supported knowledge integration, using a systematic review case study to examine when integration can extend beyond reported findings. We reviewed 37 studies on climate change, violent conflict, and household food security. Literature-based synthesis enabled integration across all included studies, whereas access to reusable outputs was limited: over half provided no data availability statement, 27% reported availability upon request, but reusable data and workflows were available for only 8%. To explore infrastructure-supported integration, we used the TIB Knowledge Loom to represent studies with accessible data and code as machine-readable outputs, and produced a knowledge gap map (KGM) from manually extracted and Loom-derived data, comparing manual and infrastructure-supported synthesis. Where outputs were reusable, synthesis could be produced directly from data and workflows rather than from publications. These findings show that literature-based synthesis can be complemented by infrastructure-supported integration where outputs are accessible and usable, and that advancing knowledge integration depends not only on infrastructures but on making data, code, and workflows accessible, executable, and reusable.
