Data Sharing Policy
At De Gruyter, we firmly believe that open access and open research are the future of academic journal publishing.
The policy below applies to De Gruyter. View Brill's data sharing policy on brill.com.
Sharing your research data
Sharing of research data demonstrates the robustness and validity of the research presented in an article by allowing others to reproduce and question results and to reuse the data for teaching and further research. It builds integrity and openness as part of the fabric of the research. For the researcher there are multiple benefits, including increasing exposure to their work.
De Gruyter is collaborating with researchers, institutes, funders, repositories, and other research data infrastructure parties to make data sharing the new normal. As a member of the STM Research Data Program initiative we are participating in the drive to achieve the harmonization and standardization of the research data ecosystem. We follow the guidelines of the 6-policies framework developed by the Research Data Alliance (RDA).
De Gruyter has implemented 4 levels of research data policies, with policy 1 being the most moderate, encouraging the provision of research data, and policy 4 being the most stringent, mandating data sharing which may be peer reviewed as part of the submission process. Please refer to the policies adopted by each journal – journals that have implemented tier 3 or 4 may have individual components integrated to their policies. This information and further instructions for submission of manuscripts can be found on the SUBMIT tab of the journal's homepage.
Feature | Publication of DAS | Sharing of data | Example journals | |
| Tier 1 | Provides basic information on Data Sharing | Optional | Optional | Historische Zeitschrift, Journal of the Bible and its Reception, Journal of Contemporary Drama in English |
| Tier 2 | Data Sharing is encouraged | Optional | Optional | Advanced Nonlinear Studies, International Journal of Adolescent Medicine and Health, Open Philosophy |
| Tier 3 | Data Sharing is expected | Required | Optional | Open Computer Science, Journal of Pediatric Endocrinology and Metabolism, Clinical Chemistry and Laboratory Medicine |
| Tier 4 | Data Sharing is mandatory | Required | Required | Cognitive Linguistics |
We acknowledge that not every journal is data-oriented, and it is not always possible to share research data publicly, for instance when privacy of research participants could be compromised. Nevertheless, we provide guidance for authors who want or need to make their research data publicly available (Sherpa-Juliet may help you find out whether your funder has an open data policy). In this way, De Gruyter intends to help authors and journals to comply with funder mandates, to increase the visibility and connectivity of their articles and data, and to improve reader and author service with more consistent links to data.
Archiving and citing your research data
Good scientific practice requires the archived data to be “FAIR”: Findable, Accessible, Interoperable, and Reusable. We recommend the use of community-endorsed data types. If you assign a persistent identifier to your research data by archiving it in a data repository, other researchers will be able to cite your data as well as your published research article.
Where possible, data should be submitted to discipline-specific, community-recognized repositories. In cases where there is no appropriate discipline-specific resource, data may be submitted to a general data repository. Please see https://www.re3data.org/, https://fairsharing.org/, or https://repositoryfinder.datacite.org/ for help finding research data repositories. We strongly recommend using CoreTrustSeal certified repositories.
Data Availability Statements (DAS) provide information on where research data that support the results and analysis can be found. It may contain links to publicly archived datasets, descriptions of the available data and/or information on how to access non-public data. Authors are responsible for providing truthful and verifiable information in this section.
If your journal uses a double-anonymized peer review process, the information in your DAS could potentially compromise the anonymity of you or your co-authors. We therefore recommend using repositories that allow temporary preservation of author anonymity to enable double-anonymized data submission (e.g. Open Science Framework, figshare, Dryad or Zenodo), or alternatively contact the curators of your data repository and ask for advice. Once accepted, please remember to replace the temporary link with a permanent live link to the data in the final version for publication – both in the DAS and cited in the reference list.
Data Availability Statements must take one of the following forms (or a combination of more than one if required for multiple types of research data):
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] |
| Data available within the article or its supplementary materials | The authors confirm that the data supporting the findings of this study are available within the article [and/or] its supplementary materials. |
| Embargo on data due to commercial restrictions | The data that support the findings will be available in [repository name] at [URL / DOI link] following a [X month] embargo from the date of publication to allow for commercialization of research findings. |
| Data available on request due to privacy/ethical/legal/ commercial restrictions | The data that support the findings of this study are available on request from the corresponding author, [initials]. The data are not publicly available due to privacy/ethical/legal/commercial restrictions. |
| Data not available - participant consent | The participants of this study did not give written consent for their data to be shared publicly, so due to the sensitive nature of the research supporting data is not available. |
| 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, [author initials], upon reasonable request. |
| Data sharing not applicable – no new data generated, or the article describes entirely theoretical research | Data sharing is not applicable to this article as no new data were created or analyzed in this study. |
| Non-digital data available | Non-digital data supporting this study are curated at [add location]. |
| Author elects to not share data | Research data are not shared. |
When data is available and linked, authors will need to provide a citation of the data in their reference list. Data citations must be included in the reference list, include the minimum information as stated below (as recommended by DataCite) and follow journal style. Please note, the term [data] will be removed before publication. We strongly suggest the use of Digital Object Identifier (DOI) links.
Data citation:
[data] Dataset creator; Year; Dataset title; Data repository or archive; Version (if any); Persistent identifier (e.g. DOI)
