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Abstract

This study contributes to the recent discussions on indicating interdisciplinarity, that is, 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.

Source

Journal of the Association for Information Science and Technology. 74(2023) no.11, S.1325-1340

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Abstract

Scientific papers are essential manifestations of evolving scientific knowledge, and arguments are an important avenue to communicate research results. This study aims to understand how the argumentation process is represented in scientific papers, which is important for knowledge representation, discovery, and retrieval. First, based on fundamental argument theory and scientific discourse ontologies, a coding schema, including 17 categories was constructed. Thereafter, annotation experiments were conducted with 40 scientific articles randomly selected from two different research areas (library and information science and biomedical sciences). Statistical analysis and the sequential pattern mining method were then employed; the ratio of different argumentation units and evidence types were calculated, the argumentation semantics of figures and tables analyzed, and the argumentation structures extracted. A correlation analysis between argumentation and rhetorical structures was also performed to further reveal how argumentation was represented within scientific discourses. The results indicated a difference in the proportion of the argumentation units in the two types of scientific papers, as well as a similar linear construction with differences in the specific argument structures of each knowledge domain and a clear correlation between argumentation and rhetorical structure.

Source

Journal of the Association for Information Science and Technology. 73(2022) no.6, S.863-878

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Source

Journal of the Association for Information Science and Technology. 73(2022) no.9, S.1201-1221

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Source

Journal of the Association for Information Science and Technology. 74(2023) no.13, S.1515-1531