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David Schindler
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Journal Articles
Publisher: Journals Gateway
Quantitative Science Studies (2024) 5 (3): 637–667.
Published: 01 August 2024
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Software is a central part of modern science, and knowledge of its use is crucial for the scientific community with respect to reproducibility and attribution of its developers. Several studies have investigated in-text mentions of software and its quality, while the quality of formal software citations has only been analyzed superficially. This study performs an in-depth evaluation of formal software citation based on a set of manually annotated software references. It examines which resources are cited for software usage, to what extent they allow proper identification of software and its specific version, how this information is made available by scientific publishers, and how well it is represented in large-scale bibliographic databases. The results show that software articles are the most cited resource for software, while direct software citations are better suited for identification of software versions. Moreover, we found current practices by both publishers and bibliographic databases to be unsuited to represent these direct software citations, hindering large-scale analyses such as assessing software impact. We argue that current practices for representing software citations—the recommended way to cite software by current citation standards—stand in the way of their adoption by the scientific community, and urge providers of bibliographic data to explicitly model scientific software.
Includes: Supplementary data
Journal Articles
Publisher: Journals Gateway
Quantitative Science Studies (2023) 4 (4): 820–838.
Published: 01 November 2023
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As an essential mechanism of scientific self-correction, articles are retracted for many reasons, including errors in processing data and computation of results. In today’s data-driven science, the validity of research data and results significantly depends on the software employed. We investigate the relationship between software usage and research validity, eventually leading to article retraction, by analyzing software mentioned across 1,924 retraction notices and 3,271 retracted articles. We systematically compare software mentions and related information with control articles sampled by coarsened exact matching by recognizing publication year, scientific domain, and journal rank. We identify article retractions caused by software errors or misuse and find that retracted articles use less free and open-source software, hampering reproducible research and quality control. Moreover, such differences are also present concerning software citation, where retracted articles less frequently follow software citation guidelines regarding free and open-source software.
Includes: Supplementary data