10.18453/rosdok_id00004777 Schindler, David David Schindler http://d-nb.info/gnd/1365103358 https://orcid.org/0000-0003-4203-8851 Universität Rostock 2024 004 Data processing Computer sciences 020 Library & information sciences 2024 en https://purl.uni-rostock.de/rosdok/id00004777 urn:nbn:de:gbv:28-rosdok_id00004777-1 This thesis develops a method to systematically analyze software in scientific publications based on an automatic information extraction pipeline applied at a large scale. Software has become increasingly important in data-driven research and plays an integral role in today's science. Knowledge of how software is applied in scientific investigations is essential to the scientific community. However, knowledge of software application in research is sparse, with a majority of information on software usage being informally described in the textual descriptions of scientific research.