This study contributes to the recent discussions on indicating interdisciplinarity, i.e., going beyond catch-all metrics of interdisciplinarity. We propose a contextual framework to improve the granularity and usability of the existing methodology for interdisciplinary knowledge flow (IKF) in which scientific disciplines import and export knowledge from/to other disciplines. To characterize the knowledge exchange between disciplines, we recognize three aspects of IKF under this framework, namely, broadness, intensity, and homogeneity. We show how to utilize them to uncover different forms of interdisciplinarity, especially between disciplines with the largest volume of IKF. We apply this framework in two use cases, one at the level of disciplines and one at the level of journals, to show how it can offer a more holistic and detailed viewpoint on the interdisciplinarity of scientific entities than aggregated and context-unaware indicators. We further compare our proposed framework, an indicating process, with established indicators and discuss how such information tools on interdisciplinarity can assist science policy practices such as performance-based research funding systems and panel-based peer review processes.

翻译：本研究旨在为近期关于跨学科性指示（即超越笼统的跨学科性指标）的讨论做出贡献。我们提出一个情境化框架，以提升现有跨学科知识流动（IKF）方法论的粒度与可用性，其中科学学科从其他学科输入知识并向其输出知识。为表征学科间的知识交换，我们在此框架下识别IKF的三个维度，即广度、强度与同质性。我们展示了如何利用这些维度揭示不同形式的跨学科性，尤其是在IKF体量最大的学科之间。我们将该框架应用于两个用例——一个在学科层面，另一个在期刊层面——以展示其相较于聚合且脱离情境的指标，如何为科学实体的跨学科性提供更全面细致的视角。我们进一步将所提出的框架（一种指示过程）与既有指标进行比较，并讨论此类跨学科性信息工具如何辅助科学政策实践，如基于绩效的研究资助体系与专家小组同行评审流程。