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：本研究为近期关于跨学科性表征的讨论做出贡献，即超越笼统的跨学科性指标。我们提出一个情境化框架，以提升现有跨学科知识流动（Interdisciplinary Knowledge Flow, IKF）方法论——即科学学科之间相互输入/输出知识的过程——的粒度与可用性。为刻画学科间的知识交换，我们在该框架下识别出IKF的三个方面：广度、强度与同质性。我们展示如何利用这些方面揭示不同形态的跨学科性，尤其是那些具有最大IKF体量的学科之间的跨学科性。我们将此框架应用于两个用例——学科层级与期刊层级——以说明相较于聚合性、无情境意识的指标，该框架如何能为科学实体的跨学科性提供更全面、更细致的视角。我们进一步将提出的框架（一种表征过程）与既有指标进行比较，并探讨此类跨学科性信息工具如何辅助科研政策实践，例如基于绩效的研究资助体系及小组制同行评审流程。