This study contributes to the recent discussions on indicating interdisciplinarity, i.e., going beyond catch-all metrics of interdisciplinarity. We propose a multi-dimensional and contextual framework to improve the granularity and usability of the existing methodology for quantifying the 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 dimensions under this framework, namely, broadness, intensity, and heterogeneity. We show that each dimension covers a different aspect of IKF, especially between disciplines with the largest volume of IKF, and can assist in uncovering different types of interdisciplinarity. 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 unidimensional 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：本研究对近期关于指示跨学科性的讨论做出贡献，即超越跨学科性的笼统指标。我们提出一个多维且情境化的框架，以提升现有方法论在量化学科间知识流动（Interdisciplinary Knowledge Flow, IKF）中的粒度与可用性——该方法论旨在刻画学科间知识的输入与输出。为表征学科间的知识交换，我们在该框架下识别三个维度，即广度、强度与异质性。研究表明，每个维度覆盖了IKF的不同方面，尤其是在知识流量最大的学科之间，且有助于揭示不同类型的跨学科性。我们将此框架应用于两个案例——一个在学科层面，另一个在期刊层面——以展示相较于单维度且缺乏情境意识的指标，该框架如何为科学实体的跨学科性提供更全面、更细致的视角。此外，我们将所提出的框架（即一种指示过程）与既有指标进行比较，并讨论此类关于跨学科性的信息工具如何有助于科学政策实践，例如基于绩效的研究资助体系及小组同行评审流程。