Reviewer Checklist For Data Release

Data Release criteria

  • Is the language of sufficient quality?

Although the editorial team may also assess the quality of the written English, please do comment if you consider the standard is below that expected for a scientific publication.

  • Is the data all available and does it match the descriptions in the paper? 

Credit should be given for transparency and provision of all supporting information.

  • Is the data and metadata consistent with relevant minimum information or reporting standards?

This is an essential component as ease of reproducibility and usability are key criteria for manuscript publication. Have the authors followed and used reporting checklists recommended in our page on the FAIRsharing network and if the methods are amenable, have the authors used workflow management systems such as Galaxy, or one of the many related systems listed on MyExperiment. We can also host these in our GigaGalaxy server if they currently do not have a home. We also encourage use of virtual machines and containers such as Docker. And the use and deposition of both wet-lab and computational protocols in a protocols repository like, and code in the cloud-based computational reproducibility platform CodeOcean

  • Is the data acquisition clear, complete and methodologically sound? 

Please remark on whether the methods are clear and if more detail should be included.  Please note, the methodology sections should never contain “protocol available upon request” or “e-mail author for detailed protocol”.

  • Is there sufficient detail in the methods and data-processing steps to allow reproduction?

Please remark on the suitability of the methods for the study.  Please note, the methodology sections should never contain “protocol available upon request” or “e-mail author for detailed protocol”.

  • Is there sufficient data validation and statistical analyses of data quality?

Please remark on the suitability of the statistics for the study. If statistical analyses have been carried out, please indicate if you feel they need to be assessed specifically by an additional reviewer with statistical expertise. 

  • Is the validation suitable for this type of data? 

Please comment on any improvements that could be made to the study design to enhance the quality of the results. If any additional experiments are required, please give details. If novel experimental techniques were used please pay special attention to their reliability and validity.

  • Is there sufficient information for others to reuse this dataset or integrate it with other data?

Please comment if any accessions are missing and should be included.

Following community standards for data sharing is a requirement of the journal. Additionally, data sharing in the broadest possible manner expands the ways in which data and tools can be accessed and used.