This means that researchers must make their datasets publicly available, whereby readers can “reach the conclusions drawn in the manuscript” and “replicate the reported study findings in their entirety.”
Datasets can be made publicly available in three ways:
In the article itself: For small datasets that can be presented in full in a table.
In the supporting information: For medium-sized datasets that can be presented in large tables or compressed files, which can be downloaded online from the journal website.
In a data repository: for large datasets (e.g., DNA sequences) that need large database infrastructures to store them.
Red Flower Publication is encouraging all journals to adopt one of the standard research data sharing policies. All Red Flower Publication journals are implementing the data citation policy. You can access the list of journals and the policies they support at the ‘Author Compliance Tool’.
Where data are held in repositories, the choice of license will be determined by the terms of the repository. Some funders also have specific license requirements. Authors are responsible for reviewing the license agreements during submission.
Researchers should ideally decide how their research data is made available, but can only share data they are legally permitted to share or make public. In general, a license that enables the maximum potential for reuse, such as one of the ‘Creative Commons Attribution-Non Commercial 4.0 International License’, is preferred. It is the responsibility of the author depositing data to confirm they have the necessary rights to submit data to a repository or journal.
Authors are encouraged to make research data available as early as possible, in accordance with community practice and as required by funder and institutional policy. Practice varies by field, and embargoes on data sharing are common practice in some communities so, in the absence of funder mandate, the relevant community standards should prevail. Only the “mandates data sharing” policy requires data sharing as a condition for publication and requires data sharing upon acceptance by the journal – authors should confirm the policy of their target journal prior to submission.
Authors are required to provide a data availability statement, including a link to the repository they have used, and to cite the data they have shared. Whenever possible the scripts and other artefacts used to generate the analyses presented in the paper should also be publicly archived.
Red Flower Publication’s Data Sharing Policies
Red Flower Publication is committed to a more open research landscape, facilitating faster and more effective research discovery by enabling reproducibility and verification of data, methodology and reporting standards. We encourage authors of articles published in our journals to share their research data including, but not limited to: raw data, processed data, software, algorithms, protocols, methods, materials.
A data availability statement confirms the presence or absence of shared data.
Links to data in data availability statements are checked to ensure they link to the data that the authors intended. If data have been shared in a data repository, the data availability statement includes a permanent link to the data. Shared data is also cited.
Quality and/or replicability of linked data are peer reviewed. Depending on the journal, this may be to peer review the quality of the data by ensuring that the results in the paper and the data in the repository align (for example, sample sizes and variables match), or it may be to peer review the replicability of the data to ensure that the claims presented in the journal article are valid and can be reproduced.
Encourages Data Sharing
The Red Flower Publication encourages authors to share the data and other artefacts supporting the results in the paper by archiving it in an appropriate public repository. Authors may provide a data availability statement, including a link to the repository they have used, in order that this statement can be published in their paper. Shared data should be cited.” All accepted manuscripts may elect to publish a data availability statement to confirm the presence or absence of shared data. If you have shared data, this statement will describe how the data can be accessed, and include a persistent identifier (e.g., a DOI for the data, or an accession number) from the repository where you shared the data. You may use the Standard Templates for Author Use or draft your own.
Expects Data Sharing
The Red Flower Publication expects that data supporting the results in the paper will be archived in an appropriate public repository. Authors are required to provide a data availability statement to describe the availability or the absence of shared data. When data have been shared, authors are required to include in their data availability statement a link to the repository they have used, and to cite the data they have shared. Whenever possible the scripts and other artefacts used to generate the analyses presented in the paper should also be publicly archived. If sharing data compromises ethical standards or legal requirements then authors are not expected to share it.
Mandates Data Sharing
The Red Flower Publication requires, as a condition for publication, that the data supporting the results in the paper will be archived in an appropriate public repository. Authors are required to provide a data availability statement, including a link to the repository they have used, and to cite the data they have shared. Whenever possible the scripts and other artefacts used to generate the analyses presented in the paper should also be publicly archived. Exceptions may be granted at the discretion of the editor, for example, if sharing data compromises privacy of human data, ethical standards or legal requirements. If authors are unable to share data (for example, if sharing data compromises ethical standards or legal requirements) then authors are not required to share it and must describe restrictions in their data availability statement.
Mandates Data Sharing and Peer Reviews Data
The Red Flower Publication requires, as a condition for publication, that the data supporting the results in the paper will be peer reviewed and archived in an appropriate public repository. Authors are required to provide a data availability statement, including a link to the repository they have used, and to cite the data they have shared. Whenever possible the scripts and other artefacts used to generate the analyses presented in the paper should also be publicly archived. Exceptions may be granted at the discretion of the editor. If sharing data compromises ethical standards or legal requirements then authors are not required to share it.
And:
Peer review of empirical data will be conducted to confirm the quality of the shared data, for example, that sample sizes match, that the variables described in the article are present as fields in the data repository, that data is complete; that data is properly labelled and described; and that it has the appropriate metadata for the kind of data being shared.
Or:
Peer review of empirical data will be conducted to confirm that the data reproduce the analytic results reported in the paper.
Standard Templates for Author Use
Below is a list of standard templates for the text that will appear in the "Data Availability Statement" portion of your article. These statements adhere to guidelines set forth to comply with journals that have an "Expects Data" or "Mandates Data" policy.
Availability of data
Template for data availability statement
Data openly available in a public repository that issues datasets with DOIs
The data that support the findings of this study are openly available in [repository name e.g “figshare”] at http://doi.org/[doi], reference number [reference number].
Data openly available in a public repository that does not issue DOIs
The data that support the findings of this study are openly available in [repository name] at [URL], reference number [reference number].
Data derived from public domain resources
The data that support the findings of this study are available in [repository name] at [URL/DOI], reference number [reference number]. These data were derived from the following resources available in the public domain: [list resources and URLs]
Embargo on data due to commercial restrictions
The data that support the findings will be available in [repository name] at [URL / DOI link] following an embargo from the date of publication to allow for commercialization of research findings.
Data available on request due to privacy/ethical restrictions
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
Data subject to third party restrictions
The data that support the findings of this study are available from [third party]. Restrictions apply to the availability of these data, which were used under license for this study. Data are available [from the authors / at URL] with the permission of [third party].
Data available on request from the authors
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Data sharing not applicable – no new data generated
Data sharing is not applicable to this article as no new data were created or analyzed in this study.
Author elects to not share data
Research data are not shared.
Data available in article supplementary material
The data that supports the findings of this study are available in the supplementary material of this article
Data sharing not applicable – no new data generated, or the article describes entirely theoretical research
Data sharing not applicable to this article as no datasets were generated or analysed during the current study
When data is available and linked, authors must provide a data citation in their reference list, formatted as :
Data citation:
[Dataset] Authors; Year; Dataset title; Data repository or archive; Version (if any);
Persistent identifier (e.g. DOI), noting that the term [Dataset] will be removed before publication.
How to choose an appropriate data repository
See below for Red Flower Publication’s recommended methods of choosing an appropriate data repository for your research:
Visit re3data.org or fairsharing.org to help identify registered and certified data repositories relevant to your subject area
