Journal Production Guidance for Software and Data Citations

Shelley Stall*, Geoffrey Bilder, Matthew Cannon, Neil P Chue Hong, Scott Edmunds, Christopher Erdmann, Michael Evans, Rosemary Farmer, Patricia Feeney, Michael Friedman, Matthew Giampoala, R. Brooks Hanson, Melissa Harrison, Dimitris Karaiskos, Daniel S. Katz, Viviana Letizia, Vincent Lizzi, Catriona MacCallum, August Muench, Kate PerryHoward Ratner, Uwe Schindler, Brian Sedora, Martina Stockhause, Randy Townsend, Jake Yeston, Timothy Clark

*Corresponding author for this work

Research output: Contribution to journalComment/debatepeer-review

Abstract / Description of output

Software and data citation are emerging best practices in scholarly communication. This article provides structured guidance to the academic publishing community on how to implement software and data citation in publishing workflows. These best practices support the verifiability and reproducibility of academic and scientific results, sharing and reuse of valuable data and software tools, and attribution to the creators of the software and data. While data citation is increasingly well-established, software citation is rapidly maturing. Software is now recognized as a key research result and resource, requiring the same level of transparency, accessibility, and disclosure as data. Software and data that support academic or scientific results should be preserved and shared in scientific repositories that support these digital object types for discovery, transparency, and use by other researchers. These goals can be supported by citing these products in the Reference Section of articles and effectively associating them to the software and data preserved in scientific repositories. Publishers need to markup these references in a specific way to enable downstream processes.
Original languageEnglish
Article number656
JournalScientific Data
Issue number1
Publication statusPublished - 31 Dec 2023


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