Data, Code, & Protocol Sharing Policy

** This can be downloaded as a pdf document here.**

As an open access journal, not only do we want to make sure that the work published in our journal is open and freely accessible for all, we also want to support as best possible the visibility and reproducibility as well as the further development of the work published in this journal. Thus, all authors are encouraged, but not required, to share their research data, code, and experimental protocols via public repositories. We do however require that all published papers include a “Data and Code Availability” statement. The decision to publish will not be affected by whether or not authors share their research data, code and/or protocols[1].

We understand that the sharing of data, code, and/or protocols is not always possible. Exceptions to this include quantitative or qualitative data that could identify a research participant unless research participants have consented to data release, sensitive data, or when there are legal, commercial, or ethical reasons present. When there are restrictions on the ability to share, these restrictions should be explained in the statement that accompanies the published paper[1].

Data Deposition

This policy applies to the research data that would be required to verify the results of research reported in articles published in the journal. Research data include data produced by the authors (“primary data”) and data from other sources that are analyzed by the authors in their study (“secondary data”). Research data includes any recorded factual material that are used to produce the results in digital and non-digital form. This includes tabular data, code, images, audio, documents, video, maps, raw and/or processed data[1].

Research data that are not required to verify the results reported in the articles are not covered by this policy. This policy does not require public sharing of quantitative or qualitative data that could identify a research participant unless participants have consented to data release. The policy also does not require public sharing of other sensitive data, such as the location of endangered species. Alternatives to public sharing of sensitive or personal data include[1]:

  • Deposition of research data in controlled access repositories
  • Anonymization or deidentification of data before public sharing
  • Only sharing metadata about the research data
  • Stating the procedures for accessing your research data in your article and managing data access requests from other researchers.

Embargoes on data sharing are permitted[1].

The preferred mechanism for sharing research data is via data repositories. When choosing the repository, we recommend choosing one that has been labelled as trustworthy and which meets set criteria, such as those by the Centre for Research Libraries or which possess a Data Seal of Approval. The chosen repository should be publicly available and without restriction, apart from those controls needed to ensure human privacy and biosafety. The repository should not be a personal, laboratory or institutional one; however, if the data needs to remain confidential until official publication, this will be accepted as long as the reviewers are allowed access if requested. In such instances, the data should be moved to a public repository at the time of online publication. Please note that InterPore Journal will not host data for authors.

The data should be uploaded into the repository in such a format so as to allow it to be re-used, and in alignment with the accepted norms for the related scientific field. Data may also be released at multiple levels if this improves upon the possibility for re-use. If the data originates from a third-party source, information on the source should be included, including how the raw data were obtained or generated, and the dates on which the date was accessed/obtained/downloaded. When possible or applicable, observation identifiers in the raw data should be disclosed. Information should also be included regarding how other researchers can access the data.

For help in finding an applicable repository, please see here.

We also request that authors cite any publicly available research data in their reference list. References to datasets (data citations) must include a persistent identifier (such as a DOI). Citations of datasets, when they appear in the reference list, should include the minimum information recommended by DataCite and follow journal style (APA)[1].

We encourage authors to make their research data available under open licenses that permit reuse freely. The journal does not enforce any particular license for research data, where research data are deposited in third party repositories, nor does publisher claim copyright in research data[1].

The journal requires authors to include in any articles that report results derived from research data to include a Data Availability statement. The provision of a Data Availability statement will be verified as a condition of publication. Data Availability statements should include information on where data supporting the results reported in the article can be found including, where applicable, hyperlinks to publicly archived datasets analyzed or generated during the study. Where research data are not publicly available, this must be stated in the manuscript along with any conditions for accessing the data. Data Availability statements should take one of the following forms (or a combination of more than one if required for multiple types of research data)[1]:

  • The datasets generated during and/or analysed during the current study are available in the [NAME] repository, [PERSISTENT WEB LINK TO DATASETS]
  • The datasets generated during and/or analysed during the current study are not publicly available due [REASON WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request.
  • The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
  • Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
  • All data generated or analysed during this study are included in this published article [and its supplementary information files].
  • The data that support the findings of this study are available from [third party name] but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of [third party name].

* Our policies in relation to data sharing are in good part taken from the following document, which which is available for public use via CC BY 4.0 license: Hrynaszkiewicz, I, Simons, N, Hussain, A, Grant, R and Goudie, S. 2020. Developing a Research Data Policy Framework for All Journals and Publishers. Data Science Journal, DOI:

Code Deposition

Similar to our policy on data sharing, we also encourage the sharing of any code, especially if it was author-generated code, that was used in performing your work. Code which has been used within a commercial software package and which is related to the findings presented in your study should also be shared, along with the name of the software package and its version. This can be noted either in the Materials and Methods or the “Data and Code Availability” Statement.

This may not always be possible, for instance due to ethical, legal, commercial, technical or practicality (requires supercomputers, specialized hardware, or very lengthy running times) reasons. In such cases, please state the reasons for this in your “Data and Code Availability” statement.

When possible, authors should deposit their code into a permanent, public repository that issues a permanent identifier number and allows for version control. If possible, we also recommend that authors have their code licensed so that it conforms with the Open-Source Definition. When depositing one’s code in a repository, the following items should also be included:

  • Information on how to install and use
  • The operating system which was used when obtaining your results
  • Information on the utilized programming language and data formats
  • Any software programs (including version and any special toolboxes, modules, packages or commands) which were used when generating your data
  • Other documentation which may be needed so that others may build upon or reproduce your work, including an explanation of the purpose of each section of code
  • The actual data used or a sample data set along with the log files which were generated when running the actual data or equivalent documentation such as screen shots

When submitting your manuscript, the following information should be included in your “Data and Code Availability Statement”: a description of the code, details of its location, including an identifier, and how to access. Should there be any restrictions on access, the restrictions should be described in this statement and information on how one could request access should be provided. Information should also be included on the programs which were used alongside this code.

* Authors are not required or expected to provide any assistance or support to others in the use of any data or code which have been made available.

Experimental Protocol Deposition

We also encourage our authors to share their step-by-step protocols that were used when conducting their research. This will also support others in replicating or building upon the author’s work. This can also be done via a protocol sharing platform of choice, or as Supplementary Material. When deposited in a repository, please provide any identifying information, such as a DOI, if present as well as all other details which would help in finding the protocols.

For questions on this policy please contact the Managing Editor at Laura.Lenz@InterPore.Org.


[1] The text in this section has been taken in large part from the following document, which is available for public use via CC BY 4.0 license: Hrynaszkiewicz, I, Simons, N, Hussain, A, Grant, R and Goudie, S. 2020. Developing a Research Data Policy Framework for All Journals and Publishers. Data Science Journal, DOI: