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Journal Production Guidance for Software and Data Citations
  • +24
  • Shelley Stall,
  • Geoffrey Bilder,
  • Matthew Cannon,
  • Neil Chue Hong,
  • Scott Edmunds,
  • Christopher C. 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 Perry,
  • Howard Ratner,
  • Uwe Schindler,
  • Brian Sedora,
  • Martina Stockhause,
  • Randy Townsend,
  • Jake Yeston,
  • Timothy Clark
Shelley Stall

Corresponding Author:[email protected]

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Geoffrey Bilder
Crossref
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Matthew Cannon
Taylor & Francis
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Neil Chue Hong
University of Edinburgh, Software Sustainability Institute
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Scott Edmunds
GigaScience Press
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Christopher C. Erdmann
Michael J. Fox Foundation
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Michael Evans
F1000Research
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Rosemary Farmer
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Patricia Feeney
Crossref
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Michael Friedman
American Meteorological Society
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Matthew Giampoala
American Geophysical Union
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R. Brooks Hanson
American Geophysical Union
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Melissa Harrison
European Molecular Biology Laboratory - European Bioinformatics Institute
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Dimitris Karaiskos
Atypon
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Daniel S. Katz
University of Illinois Urbana-Champagne
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Viviana Letizia
Elsevier
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Vincent Lizzi
Taylor & Francis
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Catriona MacCallum
Hindawi
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August Muench
American Astronomical Society
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Kate Perry
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Howard Ratner
CHORUS
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Uwe Schindler
PANGAEA, University of Bremen
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Brian Sedora
American Geophysical Union
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Martina Stockhause
DKRZ, IPCC DDC
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Randy Townsend
Plos
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Jake Yeston
Science/AAAS
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Timothy Clark
University of Virginia
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Abstract

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 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. With the current intensive use of software, including specialized tools and models for scientific research problems, the research community has begun to recognize that software, as a key research result and resource, requires the same level of transparency, accessibility, and disclosure as data.
Software and data that support scientific results should be preserved and shared in scientific repositories for discovery, transparency, and use by other researchers. These goals can be supported by citing these products in the Reference Section of papers and effectively associating them to the software and data preserved in scientific repositories. Publishers need to mark up these references in a specific way to enable downstream processes, specifically those that enable automated attribution.
Academic publishers wishing to stay current with best practices in the field are encouraged to follow the guidance provided here.
27 Dec 2022Submitted to ESS Open Archive
31 Dec 2022Published in ESS Open Archive