  Knowledge about software used in scientific investigations is important for
several reasons, for instance, to enable an understanding of provenance and
methods involved in data handling. However, software is usually not formally
cited, but rather mentioned informally within the scholarly description of the
investigation, raising the need for automatic information extraction and
disambiguation. Given the lack of reliable ground truth data, we present
SoMeSci (Software Mentions in Science) a gold standard knowledge graph of
software mentions in scientific articles. It contains high quality annotations
(IRR: $\kappa{=}.82$) of 3756 software mentions in 1367 PubMed Central
articles. Besides the plain mention of the software, we also provide relation
labels for additional information, such as the version, the developer, a URL or
citations. Moreover, we distinguish between different types, such as
application, plugin or programming environment, as well as different types of
mentions, such as usage or creation. To the best of our knowledge, SoMeSci is
the 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 use
cases and provide baseline results.
