Data Availability Policy

Journal of Responsible AI & Ethics (JRAIE)

The Journal of Responsible AI & Ethics (JRAIE) promotes transparent and responsible reporting of the availability of research data supporting published scholarly work. Authors are expected to provide sufficient information for readers, reviewers, and editors to understand whether the data underlying the findings of a manuscript are available, where they can be accessed, and whether any ethical, legal, contractual, privacy, security, or proprietary restrictions apply.

The purpose of this policy is to ensure that the availability status of research data is communicated clearly and consistently. JRAIE recognizes that public sharing is not appropriate or possible for every dataset. Accordingly, authors should provide an accurate Data Availability Statement that reflects the actual status of the data associated with the manuscript.

This policy should be read together with the journal's Research Data Sharing Policy, Publication Ethics and Malpractice Statement, Privacy Policy, Research Misconduct Policy, and applicable research-ethics requirements.

1. Scope of the Policy

This policy applies to manuscripts that rely on data collected, generated, processed, analyzed, simulated, obtained from third parties, or otherwise used as evidence for the findings or conclusions presented in the article.

Research data may include quantitative datasets, qualitative records, experimental observations, survey responses, interview data, computational outputs, statistical files, machine-learning datasets, simulation outputs, images, coded records, analytical results, software-related materials, or other resources that support the reported research.

The policy does not require authors to create or publicly release data where no research dataset exists or where legitimate restrictions prevent disclosure. However, the availability status should be stated accurately.

2. Data Availability Statement

Where applicable, submitted manuscripts should include a Data Availability Statement describing the status of the data supporting the research.

Authors submitting manuscripts involving research data should include a Data Availability Statement as part of the manuscript submission process. The statement should accurately describe the availability status of the data supporting the reported findings.

The statement should indicate whether the relevant data are:

Openly available in a public repository.
Included within the article or supplementary materials.
Available from the corresponding author upon reasonable request.
Available through controlled or restricted access.
Obtained from a third party and subject to access conditions.
Unavailable because of ethical, legal, privacy, confidentiality, security, contractual, or proprietary restrictions.
Not applicable because the manuscript does not rely on a research dataset.

Authors should avoid vague or misleading statements concerning data availability.

3. Publicly Available Data and Repositories

Where research data have been deposited in a public repository, authors should identify the repository clearly and provide an appropriate persistent identifier, accession number, dataset DOI, or stable access information where available.

The Data Availability Statement should enable readers to locate the relevant dataset without unnecessary ambiguity.

Authors should verify that repository links and identifiers are functional and correspond to the data described in the manuscript.

Authors are encouraged to use recognized data repositories appropriate to their research field. Where applicable, authors may consider discipline-specific repositories or general-purpose repositories that provide persistent identifiers, stable access, and long-term accessibility.

4. Data Included With the Article

Where all data necessary to support the findings are contained within the published article, tables, appendices, or supplementary materials, authors may state this directly.

Authors should ensure that such a statement is accurate and that no essential underlying dataset has been omitted where its absence would materially limit interpretation of the findings.

5. Data Available Upon Reasonable Request

Where public deposition is not feasible but the data may be shared directly, authors may state that the data are available from the corresponding author upon reasonable request.

This wording should be used only when the authors genuinely expect to provide access under appropriate circumstances.

A reasonable request may be subject to legitimate conditions concerning:

Participant confidentiality.
Institutional approval.
Ethics requirements.
Data-use agreements.
Security controls.
Intellectual-property rights.
Third-party permissions.
Other lawful restrictions.

Authors should not state that data are available upon request if they already know that access cannot realistically be provided.

6. Restricted or Controlled-Access Data

Some research data may require controlled access because unrestricted public release could create ethical, legal, privacy, confidentiality, or security concerns.

In such cases, authors should explain the nature of the restriction as clearly as reasonably possible without disclosing protected information.

The existence of restricted data does not automatically prevent publication where the restriction is legitimate and appropriately disclosed.

7. Human Participant and Sensitive Data

Research involving human participants, personal information, health-related information, behavioral records, biometric information, or other sensitive data requires particular attention.

Authors must not publicly disclose identifiable or potentially re-identifiable information where disclosure would violate informed consent, ethics approval, confidentiality obligations, privacy requirements, or applicable law.

Where data cannot be made publicly available, the Data Availability Statement should indicate that access is restricted because of privacy, ethical, or confidentiality considerations.

8. Artificial Intelligence and Machine-Learning Data

For studies involving artificial intelligence, machine learning, deep learning, generative AI, algorithmic systems, or automated decision-making, authors should clearly describe the availability of datasets used for model development and evaluation.

Where relevant, the Data Availability Statement should address the availability of:

Training datasets.
Validation datasets.
Test datasets.
Benchmarking data.
Annotations or labels.
Evaluation data.
Synthetic datasets.
Derived datasets.
Supporting metadata.

For computational models, AI systems, simulations, or statistical analyses, authors are encouraged to provide information regarding the availability of relevant source code, software tools, model configurations, computational workflows, or analytical materials where sharing is appropriate and legally permissible.

If some datasets, software, or analytical resources are restricted, authors should clearly explain the reason for the restriction.

9. Synthetic and Simulated Data

Where research findings are based on synthetic, simulated, generated, or artificially constructed datasets, this should be stated clearly.

Authors should indicate whether the synthetic or simulated data are publicly available, included with the article, available upon request, or reproducible from described procedures or code.

Synthetic datasets should not be presented as real-world observational data.

10. Third-Party and Proprietary Data

Where authors use data obtained from a third party, institution, organization, commercial provider, government body, or external source, they should accurately describe the access conditions.

Authors must not claim that such data are publicly available if redistribution is prohibited.

Research involving proprietary or commercially sensitive datasets should disclose relevant restrictions transparently where possible.

11. Data Supporting Results and Reproducibility

Where tables, graphs, statistical analyses, or model-performance results form an important part of the manuscript, authors should ensure that sufficient supporting information is available to understand and evaluate the findings.

Authors should provide sufficient methodological detail to explain how data were collected, prepared, analyzed, and interpreted.

Where reproducibility depends on code, software, model configurations, proprietary systems, or analytical materials, authors should disclose their availability separately where appropriate.

12. Data Documentation

Where data are made available, authors are encouraged to provide sufficient documentation to enable meaningful interpretation.

Documentation may include:

Variable descriptions.
Codebooks.
Data dictionaries.
Measurement units.
Sampling information.
Preprocessing procedures.
Missing-value conventions.
Annotation methods.
Version information.
Methodological notes.

13. Data Availability for Editorial Assessment

Editors or reviewers may request access to relevant underlying data when reasonably necessary to evaluate accuracy, methodology, reproducibility, or research integrity.

Data provided during peer review will be treated confidentially and will not be used for unrelated purposes.

14. Incorrect or Misleading Availability Statements

Authors must not provide false, inaccurate, or misleading information concerning the existence, location, accessibility, or ownership of research data.

Where serious discrepancies are identified, the matter may be evaluated under the journal's Research Misconduct Policy or applicable publication-ethics procedures.

15. Responsibilities of Authors

Authors are responsible for ensuring that the Data Availability Statement:

Accurately reflects the status of the underlying data.
Identifies relevant repositories or access routes where applicable.
Discloses legitimate access restrictions.
Respects participant privacy and confidentiality.
Does not violate contractual or legal obligations.
Appropriately identifies third-party ownership.
Remains consistent with the methodology reported in the manuscript.

16. Responsibilities of Editors

Editors should consider whether data-availability information is sufficiently clear for the type of research being reported.

Editors may request clarification regarding data sources, ownership, accessibility, ethical status, or restrictions.

Questions concerning suspected data fabrication, falsification, manipulation, or misleading availability statements should be addressed through appropriate research-integrity procedures.

17. Relationship With Research Data Sharing Policy

The Data Availability Policy focuses on disclosure of the availability status of data supporting individual manuscripts.

The Research Data Sharing Policy establishes broader principles concerning responsible data sharing, repositories, documentation, reuse, privacy, restricted data, AI-related datasets, and research-data stewardship.

Both policies should be considered together when preparing manuscripts involving research data.

Commitment to Data Transparency

The Journal of Responsible AI & Ethics (JRAIE) supports transparent reporting of research-data availability as an important element of responsible scholarly communication.

The journal seeks to balance openness, reproducibility, and accountability with legitimate obligations concerning privacy, participant protection, confidentiality, intellectual property, security, and legal compliance.

Any future changes to this policy will be communicated transparently through the journal website. Previously published articles will continue to follow the data availability terms applicable at the time of publication unless changes are required because of correction, ethical, legal, or research-integrity considerations.

Authors are expected to provide clear and truthful information regarding research-data availability and ensure that availability statements accurately reflect the conditions under which supporting evidence may be examined or reused.