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Abstract

In this study, we propose a way to link the scholarly contents of scientific papers by constructing a knowledge graph based on the semantic organization of argumentation units and relations in scientific papers. We carried out an argumentation graph data model aimed at linking multiple discourses, and also developed a semantic annotation platform for scientific papers and an argumentation graph visualization system. A construction experiment was performed using 12 articles. The final argumentation graph has 1,262 nodes and 1,628 edges, including 1,628 intra-article relations and 190 inter-article relations. Knowledge evolution representation, strategic reading, and automatic abstracting use cases are presented to demonstrate the application of the argumentation graph. In contrast to existing knowledge graphs used in academic fields, the argumentation graph better supports the organization and representation of scientific paper content and can be used as data infrastructure in scientific knowledge retrieval, reorganization, reasoning, and evolution. Moreover, it supports automatic abstract and strategic reading.

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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.