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RDFtex in-depth: knowledge exchange between LATEX-based research publications and Scientific Knowledge Graphs
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Journal Article
RDFtex in-depth: knowledge exchange between LATEX-based research publications and Scientific Knowledge Graphs
2024
Overview
For populating Scientific Knowledge Graphs (SciKGs), research publications pose a central information source. However, typical forms of research publications like traditional papers do not provide means of integrating contributions into SciKGs. Furthermore, they do not support making direct use of the rich information SciKGs provide. To tackle this, the present paper proposes RDFtex, a framework enabling (1) the import of contributions represented in SciKGs to facilitate the preparation of -based research publications and (2) the export of original contributions from papers to facilitate their integration into SciKGs. The framework’s functionality is demonstrated using the present paper itself since it was prepared with our proof-of-concept implementation of RDFtex. The runtime of the implementation’s preprocessor was evaluated based on three projects with different numbers of imports and exports. A small user study (N=10) was conducted to obtain initial user feedback. The concept and the process of preparing a -based research publication using RDFtex are discussed thoroughly. RDFtex’s import functionality takes considerably more time than its export functionality. Nevertheless, the entire preprocessing takes only a fraction of the time required to compile the PDF. The users were able to solve all predefined tasks but preferred the import functionality over the export functionality because of its general simplicity. RDFtex is a promising approach to facilitate the move toward knowledge graph augmented research since it only introduces minor differences compared to the preparation of traditional -based publications while narrowing the gap between papers and SciKGs.
Publisher
Springer Nature B.V
Subject
