Sharing practices of software artefacts and source code for reproducible research

Abstract While source code of software and algorithms depicts an essential component in all fields of modern research involving data analysis and processing steps, it is uncommonly shared upon publication of results throughout disciplines. Simple guidelines to generate reproducible source code have been published. Still, code optimization supporting its repurposing to different settings is often neglected and even less thought of to be registered in catalogues for a public reuse. Though all research output should be reasonably curated in terms of reproducibility, it has been shown that researchers are frequently non-compliant with availability statements in their publications. These do not even include the use of persistent unique identifiers that would allow referencing archives of code artefacts at certain versions and time for long-lasting links to research articles. In this work, we provide an analysis on current practices of authors in open scientific journals in regard to code availability indications, FAIR principles applied to code and algorithms. We present common repositories of choice among authors. Results further show disciplinary differences of code availability in scholarly publications over the past years. We advocate proper description, archiving and referencing of source code and methods as part of the scientific knowledge, also appealing to editorial boards and reviewers for supervision.

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Publication Details

Journal
International Journal of Data Science and Analytics
Published
2024-08-11
DOI
https://doi.org/10.1007/s41060-024-00617-7
Citations
2
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
2.10

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article

Sharing practices of software artefacts and source code for reproducible research

Fleur Jeanquartier, Sarah Stryeck, Jörg Simon, Claire Jean-Quartier et al.
2 citations
International Journal of Data Science and Analytics
Scientific Computing and Data Management
2.10
article

Sharing practices of software artefacts and source code for reproducible research

Fleur Jeanquartier, Sarah Stryeck, Jörg Simon, Claire Jean-Quartier, Ilire Hasani‐Mavriqi, Birgit Söser
article en
2 citations

Abstract

Abstract While source code of software and algorithms depicts an essential component in all fields of modern research involving data analysis and processing steps, it is uncommonly shared upon publication of results throughout disciplines. Simple guidelines to generate reproducible source code have been published. Still, code optimization supporting its repurposing to different settings is often neglected and even less thought of to be registered in catalogues for a public reuse. Though all research output should be reasonably curated in terms of reproducibility, it has been shown that researchers are frequently non-compliant with availability statements in their publications. These do not even include the use of persistent unique identifiers that would allow referencing archives of code artefacts at certain versions and time for long-lasting links to research articles. In this work, we provide an analysis on current practices of authors in open scientific journals in regard to code availability indications, FAIR principles applied to code and algorithms. We present common repositories of choice among authors. Results further show disciplinary differences of code availability in scholarly publications over the past years. We advocate proper description, archiving and referencing of source code and methods as part of the scientific knowledge, also appealing to editorial boards and reviewers for supervision.

International Journal of Data Science and AnalyticsVol. 20(3)
Graz University of Technology (AT), Research Center Pharmaceutical Engineering (Austria) (AT), BOKU University (AT)
TU Graz, Internationale Beziehungen und Mobilitätsprogramme
Openalex Percentile: Top 9%
Scientific Computing and Data Management
2.10
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