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Knowledge about software used in scientific investigations is important forseveral reasons, for instance, to enable an understanding of provenance andmethods involved in data handling. However, software is usually not formallycited, but rather mentioned informally within the scholarly description of theinvestigation, raising the need for automatic information extraction anddisambiguation. Given the lack of reliable ground truth data, we presentSoMeSci (Software Mentions in Science) a gold standard knowledge graph ofsoftware mentions in scientific articles. It contains high quality annotations(IRR: $\kappa{=}.82$) of 3756 software mentions in 1367 PubMed Centralarticles. Besides the plain mention of the software, we also provide relationlabels for additional information, such as the version, the developer, a URL orcitations. Moreover, we distinguish between different types, such asapplication, plugin or programming environment, as well as different types ofmentions, such as usage or creation. To the best of our knowledge, SoMeSci isthe most comprehensive corpus about software mentions in scientific articles,providing training samples for Named Entity Recognition, Relation Extraction,Entity Disambiguation, and Entity Linking. Finally, we sketch potential usecases and provide baseline results.

SoMeSci- A 5 Star Open Data Gold Standard Knowledge Graph of Software Mentions in Scientific Articles