Research Data & Data Sharing
Data Should Be as Open as Ethically and Legally Possible
Research data should be made as transparent and accessible as ethically, legally, and practically possible, while respecting privacy, confidentiality, intellectual property, security, and other legitimate restrictions. Authors should make supporting data available where appropriate, recognizing that legitimate restrictions may limit access.
How Data May Be Shared
The appropriate approach depends on the research — no category is inherently better than another.
Open Data
Publicly accessible through an appropriate repository.
Restricted Data
Access limited because of legitimate privacy, ethical, legal, security, or contractual considerations.
Controlled Access
Qualified researchers may obtain access through an appropriate process.
No Shareable Data
The research does not produce or rely on data that can reasonably be shared.
1. Scope
This policy may apply to research data associated with submitted and published scholarly work — quantitative and qualitative datasets, survey data, experimental and observational data, archival datasets, computational outputs, supporting materials, and code where relevant. Not every article produces a dataset; some disciplines rely primarily on textual, archival, theoretical, or other forms of evidence.
2. General Principles
- Transparency — readers should be able to understand how the research evidence was generated and, where appropriate, access supporting data
- Reproducibility — data and supporting materials should be documented sufficiently to support verification or reuse where feasible
- Ethical Responsibility — data sharing must not compromise research participants or violate ethical requirements
- Privacy — personal and sensitive information must be appropriately protected
- Security — data must be handled according to legitimate security requirements
- Responsible Reuse — researchers should respect applicable licenses, permissions, and restrictions
3. Data Availability Statements
A Data Availability Statement tells readers whether supporting data are available, where they can be accessed, any access restrictions, repository information where applicable, relevant identifiers, and — where sharing is restricted — why data cannot be shared.
“Data are available in [Repository] at [Identifier].”
“The data supporting this study are not publicly available because [verified reason].”
4. When Data Should Be Shared
Sharing is encouraged when data support published findings, sharing is ethically permissible, legal restrictions do not prevent access, participants have been appropriately protected, intellectual property restrictions are addressed, and repository access is practical. Public sharing is not required where legitimate restrictions apply.
5. Data Repositories & Citation
Repositories can provide stable access and preservation for research datasets — institutional repositories, subject repositories, general research repositories, and government or public repositories may all be appropriate depending on the research. PenScholar does not currently endorse a specific repository.
Where available, authors should provide a persistent identifier — a DOI, accession number, repository record identifier, or stable URL — and cite datasets appropriately, identifying the creator, dataset title, year, repository, and identifier, distinguishing them from ordinary references.
6. Sensitive and Personal Data
Personal, confidential, or sensitive research data — such as personally identifiable information, health information, sensitive participant data, confidential interviews, private records, or security-sensitive information — may require restricted access or may not be suitable for public release.
Human Participants and Consent
Data sharing must respect participant consent, ethical approval, privacy, confidentiality, and applicable institutional requirements. Where participant consent limits sharing, authors should explain the access restrictions.
7. Restricted or Controlled Access
Data may be restricted because of privacy, confidentiality, ethical commitments, legal restrictions, security, intellectual property, or third-party agreements. Where appropriate, authors should explain why access is restricted, whether controlled access is available, and how qualified researchers may request access — for example through institutional procedures, repository-controlled access, or data use agreements. PenScholar does not operate its own data-access committee.
Embargoes
Legitimate embargoes may sometimes apply — for reasons such as publisher agreements, funder requirements, participant protection, intellectual property, or planned publication. No fixed maximum embargo period is defined by PenScholar; authors should explain the restriction where appropriate.
8. Proprietary and Third-Party Data
Research may rely on data that authors do not own or cannot redistribute. Authors should identify relevant restrictions, provide appropriate provenance information, explain how qualified readers may access the data where possible, and respect licensing and contractual obligations — never breach a third-party agreement to satisfy this policy. Authors should distinguish original data from reused, public, licensed, and proprietary datasets, with appropriate attribution and citation.
9. Synthetic Data and Computational Research
Legitimate synthetic or simulated data are distinct from fabricated research evidence and may be used when they are genuinely part of the research methodology. Authors should explain why synthetic data were used, how they were generated, their relationship to the research question, and important limitations — synthetic data must never be presented as real-world observations.
For computational research, reproducibility may require more than a dataset — code, scripts, analysis workflows, model information, parameters, or documentation may also be relevant. Code is requested only where relevant, and authors are not required to publish proprietary software or confidential code.
10. Supporting Reproducibility
Authors should provide enough methodological and supporting information — data, code, protocols, documentation, or analytical procedures — for qualified researchers to understand and, where feasible, reproduce or assess the research. This policy does not claim that every published study can be perfectly reproduced.
11. Responsibilities
Authors Should
- Provide accurate data descriptions
- Follow ethical requirements and protect participants
- Respect data ownership
- Provide Data Availability Statements and repository information where applicable
- Cite reused datasets and explain access restrictions
- Avoid misrepresenting unavailable data as publicly accessible
Reviewers and Editors
Reviewers and editors may evaluate whether data availability claims are clear, whether statements match the manuscript, and whether restrictions are adequately explained. Reviewers are not expected to independently reproduce every dataset, and editors do not have unrestricted access to confidential datasets.
Data Quality & Formats
Shared datasets should include appropriate documentation where feasible — description, variables, methodology, collection process, file formats, and limitations. PenScholar does not prescribe one file format for every discipline.
12. Intellectual Property & Research Integrity
Data sharing must respect copyright, database rights where applicable, licenses, contracts, and third-party restrictions. Serious concerns about fabricated or falsified data, manipulated datasets, selective reporting, misrepresented data availability, or deliberate concealment of relevant evidence may raise research integrity concerns — an allegation alone does not establish that misconduct has occurred.
Copyright & Licensing Research Integrity
13. Exceptions and Reporting a Concern
Data may not be shareable when doing so would create legitimate concerns involving privacy, confidentiality, participant safety, legal restrictions, security, intellectual property, third-party agreements, or ethical obligations. An exception should never be used to conceal poor data practices — authors should explain restrictions transparently where appropriate.
Readers may report credible concerns about data availability, data integrity, dataset provenance, misrepresented data, or reproducibility.
Data Availability Checklist
Before submission, authors should confirm:
- The data availability statement accurately describes the dataset
- Any repository information is correct
- Dataset identifiers have been verified
- Sensitive information has been appropriately protected
- Third-party restrictions have been considered
- Reused datasets are properly cited
- Synthetic data are clearly identified
- Any access restrictions are explained
- Supporting code or materials are identified where relevant