How to choose an appropriate data repository

MDPI encourages the submission of data to community-recognized data repositories where possible. We recommend the authors visit re3data.org or fairsharing.org to help identify registered and certified data repositories relevant to their subject area if no community resource is available. If the authors’ institution has its generalist data repository this can be used to host authors’ data as long as the repository can mint DataCite DOIs, and allows for data to be shared under open terms of use (for example the CC0 waiver).



Supplementary Materials, Data Deposit and Software Source Code
MDPI Research Data Policies

MDPI is committed to supporting open scientific exchange and enabling our authors to achieve best practices in sharing and archiving research data. We encourage all authors of articles published in MDPI journals to share their research data including, but not limited to protocols, analytic methods, raw data, processed data, code, software, algorithms, and study material. The data should be FAIR – findable, accessible, interoperable, and reusable – so that other researchers can locate and use the data.

We recommend that data and code should be deposited in a trusted repository that will allow for maximum reuse (see the Data Preservation section below). If this is not possible, authors are encouraged to share the specific reason in the Data Availability Statement and make this material available upon request to interested researchers. In addition, research materials necessary to enable the reproduction of an experiment should be indicated in the Materials and Methods section. Individual journal guidelines can be found at the journal ‘Instructions for Authors’ page. Data sharing policies concern the minimal dataset that supports the central findings of a published study. Generated data should be publicly available and cited in accordance with journal guidelines.

MDPI data policies are informed by TOP Guidelines.

Where ethical, legal, or privacy issues are present, data should not be shared. The authors should clarify the availability status of the data upon submission and make any limitations or exceptions clear in the Data Availability Statement. Authors should ensure that the data shared is in accordance with consent provided by participants on the use of confidential data. Authors should ensure that the publication of such data does not compromise the anonymity of the participants or breach local data protection laws.

In situations where access is restricted to protect confidential or proprietary information, authors will be requested to clearly explain the restrictions on the dataset and make the data available upon request, with permission for the purposes of peer review.

MDPI recognizes that some institutions and funding agencies only require the retention of research data for a finite period after a project’s completion or publication. However, there are no such limits specified within the MDPI Data Availability Policy and, therefore, we encourage the authors to archive their research data through appropriate data repositories or provide us with minimal datasets within Supplementary Material.

Data availability statements

Data availability statements are required for all articles published with MDPI. During the peer review and editorial decision process, authors can be asked to share existing datasets or raw data that have been analyzed in the manuscript, and whether they will be made available to other researchers following publication. Authors will also be asked for the details of any existing datasets that have been analyzed in the manuscript.

Below are the recommended Data Availability Statements:

Data availability status	Recommended Data Availability Statement
Data available in a publicly accessible repository	The original data presented in the study are openly available in [repository name, e.g., FigShare] at [DOI/URL] or [reference/accession number].
Data available on request due to restrictions (e.g., privacy, legal or ethical reasons)	The data presented in this study are available on request from the corresponding author due to (specify the reason for the restriction).
3rd Party Data	Restrictions apply to the availability of these data. Data were obtained from [third party] and are available [from the authors/at URL] with the permission of [third party].
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.
Restrictions apply to the datasets	The datasets presented in this article are not readily available because [include reason, e.g., the data are part of an ongoing study or due to technical/ time limitations]. Requests to access the datasets should be directed to [text input].
Data derived from public domain resources	The data presented in 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].
Data sharing is not applicable (only appropriate if no new data is generated or the article describes entirely theoretical research)	No new data were created or analyzed in this study. Data sharing is not applicable to this article.
Data is contained within the article or supplementary material	The original contributions presented in this study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author(s).
Dataset available on request from the authors	The raw data supporting the conclusions of this article will be made available by the authors on request.
Data preservation

MDPI acknowledges that researchers, institutions, journals, and data repositories have a shared responsibility to ensure long-term data preservation, and MDPI encourages authors to select data repositories with this goal in mind.

MDPI encourages authors to commit to preserving their datasets on their laboratory or institutional servers, for at least five years after publication. If, during that time, the repository to which the data were originally submitted disappears or experiences data loss, we may ask the authors to upload the data to another repository and publish a correction or update to the original publication.

If authors remove their data from the original public repository or change access criteria in a manner that is inconsistent with the publication, we may ask authors to notify the editorial office as soon as possible.

How to choose an appropriate data repository

MDPI encourages the submission of data to community-recognized data repositories where possible. We recommend the authors visit re3data.org or fairsharing.org to help identify registered and certified data repositories relevant to their subject area if no community resource is available. If the authors’ institution has its generalist data repository this can be used to host authors’ data as long as the repository can mint DataCite DOIs, and allows for data to be shared under open terms of use (for example the CC0 waiver).

Data repository criteria

The following criteria should be considered when selecting an appropriate repository, ensuring that platforms:

Ensure long-term persistence and preservation of datasets in their published form;
Provide stable identifiers for submitted datasets (DOIs in most cases);
Allow public access to data without barriers, such as logins or paywalls;
Support open licenses (CC0 and CC-BY, or their equivalents, are required in most cases);
Provide confidential review of submitted datasets without the requirement for reviewers to provide identifying information.
Data citation

Authors are encouraged to formally cite any datasets stored in external repositories that are mentioned within their manuscript, including the main datasets that are the focus of the submission, as well as any other datasets that have been used in the work. For previously published datasets, authors should cite both the related research articles and the datasets themselves. Appropriate citation of data is checked and enforced by Journal Editorial staff before publication.

Computer Code and Software

For work where novel computer code was developed, authors should release the code either by depositing in a recognized, public repository or uploading as supplementary information to the publication. The name and version of all software used should be clearly indicated.

Supplementary Material

Additional data and files can be uploaded as "Supplementary Files" during the manuscript submission process. The supplementary files will also be available to the referees as part of the peer review process. Any file format is acceptable, however we recommend that common, non-proprietary formats are used where possible. For more information on supplementary materials, please refer to https://www.mdpi.com/authors/layout#_bookmark83.

How to choose an appropriate data repository

MDPI encourages the submission of data to community-recognized data repositories where possible. We recommend the authors visit re3data.org or fairsharing.org to help identify registered and certified data repositories relevant to their subject area if no community resource is available. If the authors’ institution has its generalist data repository this can be used to host authors’ data as long as the repository can mint DataCite DOIs, and allows for data to be shared under open terms of use (for example the CC0 waiver).


Unpublished Data

Restrictions on data availability should be noted during submission and in the manuscript. "Data not shown" should be avoided: authors are encouraged to publish all observations related to the submitted manuscript as Supplementary Material. "Unpublished data" intended for publication in a manuscript that is either planned, "in preparation" or "submitted" but not yet accepted, should be cited in the text and a reference should be added in the References section. "Personal Communication" should also be cited in the text and reference added in the References section. (see also the MDPI reference list and citations style guide).

Remote Hosting and Large Data Sets

Data may be deposited with specialized service providers or institutional/subject repositories, preferably those that use the DataCite mechanism. Large data sets and files greater than 60 MB must be deposited in this way. For a list of other repositories specialized in scientific and experimental data, please consult databib.org or re3data.org. The data repository name, link to the data set (URL) and accession number, doi or handle number of the data set must be provided in the paper. The journal Data also accepts submissions of data set papers.

References in Supplementary Files

Citations and References in Supplementary files are permitted provided that they also appear in the reference list of the main text.

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