Promotif: Jurnal Kesehatan Masyarakat (PJKM) encourages authors to make the data, code, instruments, protocols, and other materials supporting their published findings available whenever sharing is ethically, legally, technically, and culturally appropriate.
Data sharing can improve transparency, support verification and reproducibility, enable secondary analysis, reduce unnecessary duplication, and increase the public value of research. However, open sharing must not override participant consent, confidentiality, privacy, community agreements, legal obligations, intellectual-property rights, or legitimate security concerns.
Core Principles
Transparency
Authors should state clearly whether and how supporting data can be accessed.
Responsible Access
Sharing arrangements must protect participants, communities, and legitimate rights.
Reproducibility
Materials should support understanding and verification of the reported findings.
FAIR Practice
Data should be as findable, accessible, interoperable, and reusable as possible.
What May Constitute Supporting Research Data?
Depending on the study design, supporting research materials may include:
De-identified datasets Data dictionaries and codebooks Questionnaires and instruments Study protocols Statistical analysis plans R, Python, Stata, SPSS, or SAS code GIS layers and spatial files Qualitative coding frameworks Supplementary tables and figures Metadata and documentation
PJKM Data Sharing Expectation
As open as possible, as restricted as necessary: Authors are encouraged to share the minimum data and documentation necessary to understand and verify the study, while applying proportionate restrictions where open release would conflict with ethical, legal, cultural, contractual, or security requirements.
Data should preferably be deposited by the time of publication. When immediate public release is not possible, authors may use controlled access, delayed release, mediated access, or a justified statement explaining why the material cannot be shared.
Data Availability Statement
Every research article should include a clear Data Availability Statement. The statement should identify what is available, where it is available, any persistent identifier, when access begins, the applicable access conditions, and any justified restrictions.
Example 1 — Open Repository
The dataset and analysis code supporting the findings of this study are openly available in [repository name] at [DOI or persistent URL] under [licence].
Example 2 — Available on Reasonable Request
The de-identified data supporting this study are available from the corresponding author upon reasonable request and subject to ethics approval, data-use conditions, and verification of the proposed purpose.
Example 3 — Restricted Data
The data are not publicly available because they contain sensitive participant information and the consent and ethics approval do not permit public sharing. Qualified researchers may contact [data custodian] to discuss controlled access.
Example 4 — No New Data
No new datasets were generated or analysed for this article. All sources used are cited in the manuscript.
Recommended Repositories
Authors should use a trustworthy disciplinary, general-purpose, institutional, or funder-supported repository that provides persistent identifiers, metadata, clear access conditions, version control, and preservation arrangements.
General-Purpose Repositories
Examples include Zenodo, Figshare, Dryad, Harvard Dataverse, and the Open Science Framework.
Institutional Repositories
A university or research-institution repository may be suitable when it provides stable access and adequate metadata.
Disciplinary Repositories
Where available, a repository designed for the relevant field or data type is preferred.
Personal cloud storage, temporary file-transfer links, and unstable web pages are not considered adequate long-term repositories.
Sensitive Human and Health Data
Participant protection takes priority: Authors must not publicly release identifiable health information, precise locations, confidential records, genetic information, images, transcripts, or other sensitive material unless sharing is permitted by informed consent, ethics approval, applicable law, and relevant community or institutional agreements.
De-identification must be proportionate to the risk of re-identification. Removing names alone may be insufficient where combinations of demographic, geographic, clinical, genetic, or temporal variables could identify a person or small community. Controlled access may be more appropriate than public release.
Qualitative and Community-Based Research
Interview transcripts, field notes, audio, video, images, and community-derived knowledge may remain identifiable even after direct identifiers are removed. Authors must consider participant expectations, group privacy, cultural sensitivity, Indigenous or local knowledge governance, community consent, and the risk that disclosure could cause stigma, discrimination, or harm.
Code, Syntax, and Analytical Materials
Authors are encouraged to share the code, syntax, macros, workflows, model specifications, GIS procedures, and version information needed to reproduce the analysis. Shared code should be documented, organised, and tested against the reported results. Proprietary software does not prevent authors from sharing syntax or a detailed analytical workflow.
FAIR Data Principles
Findable
Use rich metadata and persistent identifiers.
Accessible
State clearly how authorised users can obtain the data.
Interoperable
Use documented, standard, and machine-readable formats where possible.
Reusable
Provide provenance, definitions, licences, and sufficient documentation.
Responsibilities
Authors
Plan data management, obtain appropriate consent, protect confidentiality, prepare documentation, deposit materials where possible, and provide an accurate Data Availability Statement.
Editors
Check whether the statement is clear, proportionate, and consistent with the manuscript's ethical and methodological context.
Reviewers
May assess whether the available materials are sufficient to evaluate the manuscript, while respecting confidentiality and access restrictions.
Editorial Assessment
1
Statement Check
The editorial team checks whether a Data Availability Statement is present and understandable.
2
Consistency Review
The statement is compared with the study design, ethics approval, consent process, and manuscript claims.
3
Clarification
Authors may be asked to provide a repository link, access conditions, documentation, or a clearer justification for restrictions.
4
Publication
The final statement is published with the article and becomes part of the scholarly record.
Acceptable Restrictions
Restrictions may be justified by:
Participant privacy or confidentiality Consent limitations Ethics committee conditions Applicable law or regulation Indigenous or community governance Contractual or data-provider restrictions Intellectual property or commercial sensitivity Security or misuse risks
Restrictions must be described honestly and should be no broader or longer than necessary. “Data unavailable” without explanation is generally insufficient.
Non-Compliance and Misrepresentation
False claims that data are available, refusal to honour stated access conditions without valid justification, concealment of material data problems, or provision of fabricated or manipulated data may be addressed under the journal's Publication Ethics, Correction and Retraction, or Research Misconduct procedures.
Standards and Guidance
Related PJKM Policies
Publication Ethics Open Access Policy Copyright Notice Correction and Retraction Policy
Policy review: PJKM may revise this policy to reflect developments in research-data governance, privacy, repository practice, technology, and publication ethics. The policy identifier, version, and last-updated date above identify the current version.
PJKM supports data sharing that is transparent, proportionate, ethically responsible, and genuinely useful for verification and future public health research.
