Data Sharing Policy

The Journal of Diabetes, Metabolism and Endocrinology recognizes that responsible data sharing strengthens scientific transparency, reproducibility, verification, and the advancement of medical research. The journal therefore encourages authors to share the data supporting their published research, whenever ethically, legally, and practically possible.

Data sharing should be conducted in a manner that protects research participants, respects confidentiality, and complies with applicable institutional, legal, and ethical requirements.

1. General Principle

Authors are encouraged to make the data underlying their published findings available to other researchers through appropriate and reliable mechanisms.

Data sharing can help researchers:

• Verify published findings.
• Reproduce analyses.
• Conduct secondary research.
• Build upon existing scientific knowledge.
• Improve research transparency.
• Reduce unnecessary duplication of research.
• Strengthen the credibility and reliability of published results.

Data sharing is encouraged but must not override obligations concerning privacy, confidentiality, informed consent, intellectual property, or applicable laws and regulations.

2. Data Availability Statement

Authors should provide a Data Availability Statement where appropriate.

The statement should clearly explain whether the supporting data are:

• Publicly available.
• Available upon reasonable request.
• Available from a recognized repository.
• Subject to access restrictions.
• Not available because of ethical, legal, privacy, or other legitimate restrictions.

Examples include:

“The data supporting the findings of this study are available from the corresponding author upon reasonable request.”

or:

“The data generated and/or analyzed during this study are available in [repository name] with the identifier [DOI/accession number].”

Where data cannot be shared, authors should provide a clear explanation.

3. Recommended Data Repositories

Where appropriate, authors are encouraged to deposit supporting datasets in reputable disciplinary, institutional, governmental, or general-purpose repositories.

Where available, authors should use repositories that provide:

• Persistent identifiers such as DOIs.
• Stable long-term access.
• Appropriate metadata.
• Access-control mechanisms.
• Data versioning.
• Clear licensing terms.

4. Data Citation

Authors should appropriately cite datasets that have been deposited in public repositories or obtained from other researchers.

A dataset should be cited in a manner that allows readers to:

• Identify the dataset.
• Locate the dataset.
• Recognize the data creators.
• Access the data where permitted.
• Distinguish the dataset from ordinary literature references.

Data citations should include a persistent identifier where available.

5. Protection of Human Participant Data

For research involving human participants, patient records, clinical information, genetic data, or other sensitive information, data sharing must comply with applicable ethical and privacy requirements.

Authors must not publicly release identifiable information without appropriate authorization and consent.

Where appropriate, authors should:

• De-identify or anonymize datasets.
• Remove unnecessary personal identifiers.
• Apply appropriate access restrictions.
• Follow the conditions of the original informed consent.
• Comply with institutional and legal data-protection requirements.

The journal may reject or require modification of a proposed data-sharing arrangement if it creates an unacceptable risk to participant privacy.

6. Clinical and Medical Data

Because the journal publishes medical and biomedical research, particular care must be taken when sharing clinical datasets.

Clinical data should be shared only where appropriate safeguards are in place.

Where direct public release is inappropriate, authors may use controlled-access repositories or provide access to qualified researchers following an appropriate review process.

7. Consent and Data Sharing

Where research involves human participants, authors should consider data-sharing requirements when obtaining informed consent.

Participants should be informed, where appropriate, about:

• Whether their data may be shared.
• The types of data that may be shared.
• Who may access the data.
• How confidentiality will be protected.
• Whether data may be reused for future research.

If consent or ethical approval restricts data sharing, authors must comply with those restrictions.

8. Restricted or Sensitive Data

Some datasets cannot reasonably be made publicly available because of:

• Patient confidentiality.
• Privacy regulations.
• Ethical restrictions.
• National or institutional regulations.
• Security concerns.
• Commercial confidentiality.
• Intellectual-property restrictions.
• Third-party data-use agreements.

Such restrictions do not automatically prevent publication.

Authors should explain the restriction transparently and, where possible, describe a mechanism through which qualified researchers may request access.

9. Data Available Upon Reasonable Request

Where authors cannot deposit data publicly but can provide controlled access, they may make the data available to qualified researchers upon reasonable request.

The authors should specify:

• Who should be contacted.
• What type of data may be available.
• Any access conditions.
• Whether ethical approval is required for secondary use.
• Any applicable data-use agreement.

The corresponding author should maintain appropriate records concerning requests and access where applicable.

10. Research Materials and Supporting Information

Where appropriate, authors are encouraged to share materials necessary to understand or reproduce the research, including:

• Research protocols.
• Statistical analysis code.
• Computational code.
• Questionnaires.
• Survey instruments.
• Experimental procedures.
• Supplementary datasets.
• Relevant methodological documentation.

Sharing should remain subject to ethical, legal, copyright, and intellectual-property restrictions.

11. Data Integrity and Accuracy

Authors remain responsible for the accuracy and integrity of datasets associated with their publications.

Shared data should correspond appropriately with the data described in the published article.

Authors should not:

• Selectively remove data to misrepresent findings.
• Alter datasets without appropriate documentation.
• Fabricate or falsify shared data.
• Misrepresent the availability of data.

Where material discrepancies are identified, the journal may investigate the matter under its research-integrity and publication-ethics policies.

12. Data Management and Documentation

Authors are encouraged to maintain appropriate documentation accompanying shared datasets.

Where practical, documentation should include:

• Dataset description.
• Variable definitions.
• Data collection methods.
• Relevant coding or analysis information.
• Data-cleaning procedures.
• Version information.
• Access conditions.
• Relevant ethical restrictions.

Adequate documentation increases the usefulness and reproducibility of shared research.

13. Intellectual Property and Third-Party Data

Data sharing must respect applicable intellectual-property rights and third-party agreements.

Authors must ensure that they have the appropriate rights or permissions to share datasets and research materials.

Where third-party restrictions prevent redistribution, authors should clearly state the restrictions and, where possible, provide information about how researchers may obtain access directly from the data owner.

14. Data Sharing During Peer Review

Editors or reviewers may request access to supporting data when necessary to evaluate the validity or integrity of a manuscript.

Authors should cooperate with reasonable requests, subject to legitimate confidentiality, privacy, legal, and ethical restrictions.

Where data cannot be provided, authors should explain the reason to the Editorial Office.

15. Data Availability and Editorial Decisions

A lack of publicly accessible data does not automatically constitute grounds for rejection when legitimate ethical, legal, privacy, or institutional restrictions apply.

However, the journal may consider the transparency and accessibility of supporting data as part of its assessment of research quality and reproducibility.

16. Post-Publication Data Concerns

If questions arise after publication regarding the availability, integrity, or accuracy of supporting data, the journal may request clarification or supporting documentation from the authors.

Depending on the findings, the journal may:

• Request additional data.
• Publish a data-availability clarification.
• Issue a correction.
• Publish an Expression of Concern.
• Initiate a research-integrity investigation.
• Consider retraction where serious problems undermine the reliability of the published findings.

17. Compliance with Publication Ethics

The journal's Data Sharing Policy is consistent with its broader commitment to research integrity, transparency, reproducibility, participant protection, and responsible data management, and is applied alongside relevant COPE and ICMJE principles.

18. Author Responsibility

By submitting a manuscript, authors are encouraged to:

• Clearly describe the availability of supporting data.
• Share relevant data whenever ethically and legally possible.
• Protect participant confidentiality.
• Respect informed-consent limitations.
• Provide appropriate data citations.
• Disclose legitimate restrictions on data access.
• Ensure that shared data are accurate and appropriately documented.

The Journal of Diabetes, Metabolism and Endocrinology encourages responsible data sharing as an important component of transparent and reproducible medical research while recognizing that ethical and privacy obligations must always take priority over unrestricted data access.