Linking Scholarly Contents: The Design and Construction of an Argumentation Graph

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.