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Are data availability statements slowing down publication processes?


KEY TAKEAWAYS

  • Data availability statements (DAS) are mandatory at IOP Publishing.
  • Verifying DAS in revised manuscripts has increased editorial processing time.
  • The likelihood of manuscripts being returned to authors for quality control reasons has also increased.

Data availability statements (DAS) have helped to improve the transparency and quality of research reporting in recent years by encouraging data sharing, and are now commonplace in manuscripts. However, this drive towards open data is coupled with a need to publish results quickly, emphasised by the COVID-19 pandemic. The challenge for publishers moving forward is to ensure extra quality control steps required for DAS do not preclude rapid data dissemination.

IOP Publishing’s 2019 data availability policy requires all accepted articles to include a DAS and a persistent identifier linking to the location of the data and licensing terms, where appropriate. In their recent article, Jade Holt and colleagues measured the impact of this policy on manuscript processing time and the number of times manuscripts were returned to authors (‘unsubmitted’) in 3 journals.

Including DAS verification in quality checks for revised manuscripts resulted in the following:

  • Editorial staff took significantly longer to complete checklists.
  • The likelihood and frequency with which manuscripts were ‘unsubmitted’ increased significantly; submissions in which authors claimed to have included data within the manuscript were the most affected.
  • The number of ‘never-unsubmitted’ manuscripts decreased overall, although this effect was partially mitigated when efforts were made to clarify DAS instructions.

Extra quality control requirements on journal manuscripts can therefore increase total processing time and, by extension, raise publishing costs. However, the small sample sizes mean results should be interpreted with caution.

Extra quality control requirements on journal manuscripts can therefore increase total processing time and, by extension, raise publishing costs.

Integrated software tools used to measure the impact of DAS on publication workflows in this study could be used to monitor new data approaches without relying on self-reporting or adding further workflow burden to editorial staff. We look forward to seeing how data sharing policies will be refined in the future to support rapid data dissemination.

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Do data sharing policies impact your publication development timelines?

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