Data sharing policy

          

Sharing data

Researchers can share the data associated with their work in an online storage space known as a repository. Repositories facilitate the advancement of science by ensuring that research data is discoverable by as many people as possible.

Veterinary Evidence encourages researchers to share their data sets within a repository. Sharing data has many benefits to scholarly research and its translation into practice. It:

  • Improves transparency of research, which facilitates validation of results and helps enable evidence-based decisions  
  • Allows others to reproduce and build upon research findings, which can lead to new discoveries   
  • Encourages collaboration between researchers

 

 

What is data?

When depositing data to a repository, authors should, at the very least, share the data that will allow others to replicate the results of the paper. Examples of data are:

  • Raw or processed data
  • Statistical methods
  • Survey results
  • Interview transcripts
  • Protocols
  • Images/photographs
  • Videos

 

Our policy

Veterinary Evidence, wherever legally and ethically possible, strongly encourages authors to share the data generated by their research by depositing it into an appropriate repository.

It is the responsibility of the authors to check whether they are able to legally and ethically submit data to a journal or repository. If in doubt, authors should contact Veterinary Evidence for more information or seek advice from their institution’s ethics committee.

Authors that submit data to a repository should provide a data availability statement within the acknowledgement section of their submission. This should include a link to the repository they have used.

Veterinary Evidence is an open access journal that publishes content under a CC BY licence. We therefore encourage authors, where possible, to make their data available under a similar liberal licence.

Many funders now require grantees to share their data sets within a repository. Authors can search and check funder requirements at SHERPA Juliet http://v2.sherpa.ac.uk/.

Data sets may be peer reviewed alongside submissions.

Data availability statement

A data availability statement provides information on where and how the data can be accessed. If for any legal or ethical reasons data cannot be publicly accessed then authors need to state how the data can be obtained.

Templates of example statements are listed below.

  1. The data that support the findings of this study are available in the repository [name of repository] at [DOI or URL], reference number [reference number].
  2. The authors confirm that the data supporting the findings of this study are available within the article [and/or] its supplementary materials.
  3. The data generated during and/or analysed within the study are available from the corresponding author(s) on reasonable request.
  4. The data that support the findings of this study are available from [third party name] but restrictions apply to the availability of the data, hence the data are not publicly available. The data generated during and/or analysed within the study are available from the corresponding author(s) on reasonable request and with permission of [third party name].

Repositories

Where possible, research data should be deposited to an appropriate discipline-specific repository, or to a general-purpose repository if no appropriate discipline-specific repository is available.

Please refer to funder requirements before depositing data to a repository.

General-purpose repositories:

Zenodo

FigShare

Dryad

Citing data sets

Veterinary Evidence adheres to the Force 11 Joint Declaration of Data Citation Principles: https://www.force11.org/datacitationprinciples

All datasets that are hosted in a public repository and used in the writing of an article should be cited in the reference list. This includes the author’s own data set if referred to in the paper.

Citing data helps enhance visibility and ensures data contributors receive proper credit.

When referencing a dataset, authors should use the following format, as recommended by DataCite:

Creator (PublicationYear). Title. Publisher. Identifier

For more information please contact the editorial office.

 

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