An Ontology-Based Approach to Model the Interconnections between Research Artifacts

Abstract

A huge amount of research artifacts (e.g. papers, journals) is published on the web, and there is an emerging need to link these artifacts in a suitable way. While this scholarly record represents a great source of knowledge, new researchers are struggling to explore these artifacts, find out the relations between them and determine how they build on each other. Without doing so, new researchers will not be able to identify research contributions. Existing digital libraries that archive research papers may provide access to references or related papers without identifying how and why these references are cited and used. While few existing works have addressed the issue of modeling research arguments (e.g. how researchers interlinked existing research efforts), few research efforts have discussed how the semantic modeling can be employed in practice to enhance the research process in practice. The approach of this study builds using an Ontology model that is main target to offer a practical evidence of the potential of modeling research arguments for researchers. Example of the solutions we aim to support by utilizing the model of research argument include: 1) classify research papers based on the degree of matching in-between them. 2) Match researchers with similar/related/complementary interests according to the research arguments they give. 3) Identify the successive research efforts that build on each other and lean to a particular research contribution. The approach of this study offers several benefits for researchers: First, it will enable researchers to quickly explore the research domain and recall the relationships between independent works rapidly. Second, it support collaborative research and brainstorming by matching and linking researchers who share the same or related interests, a thing that can be powerful to the research community.