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Scientific knowledge graphs have been proposed as a solution to structure thecontent of research publications in a machine-actionable way and enable moreefficient, computer-assisted workflows for many research activities.Crowd-sourcing approaches are used frequently to build and maintain suchscientific knowledge graphs. To contribute to scientific knowledge graphs,researchers need simple and easy-to-use solutions to generate new knowledgegraph elements and establish the practice of semantic representations inscientific communication. In this paper, we present a workflow for authors ofscientific documents to specify their contributions with a LaTeX package,called SciKGTeX, and upload them to a scientific knowledge graph. The SciKGTeXpackage allows authors of scientific publications to mark the maincontributions of their work directly in LaTeX source files. The package embedsmarked contributions as metadata into the generated PDF document, from wherethey can be extracted automatically and imported into a scientific knowledgegraph, such as the ORKG. This workflow is simpler and faster than currentapproaches, which make use of external web interfaces for data entry. Our userevaluation shows that SciKGTeX is easy to use, with a score of 79 out of 100 onthe System Usability Scale, as participants of the study needed only 7 minuteson average to annotate the main contributions on a sample abstract of apublished paper. Further testing shows that the embedded contributions can besuccessfully uploaded to ORKG within ten seconds. SciKGTeX simplifies theprocess of manual semantic annotation of research contributions in scientificarticles. Our workflow demonstrates how a scientific knowledge graph canautomatically ingest research contributions from document metadata.

SciKGTeX -- A LaTeX Package to Semantically Annotate Contributions in Scientific Publications