Data Sharing Policy

Promoting Transparency, Reproducibility, and Open Science

Prime Academic Press encourages and supports the open sharing of research data underlying all published articles. Data sharing enhances transparency, reproducibility, and citation impact, while benefiting the broader research community.

This policy applies to all research data, raw or processed, that is necessary to understand, replicate, or extend the findings reported in our journals.

Core Principles

  • Transparency: Authors should make research data openly available whenever legally and ethically possible.
  • Reproducibility: Data should be complete, documented, and citable to enable independent verification.
  • Open Access: Data should be deposited in trusted, public repositories with persistent identifiers (e.g., DOI).
  • Attribution: Data should be cited appropriately, and authors retain rights to their data.
  • Ethics & Privacy: Personal, sensitive, or restricted data must be protected in accordance with applicable laws.

Data Availability Statement (DAS)

All articles must include a clear Data Availability Statement. Authors may use one of the following standard templates, as appropriate：

1. Data available in a public repository (preferred):

The datasets generated and analyzed during the current study are available in the [REPOSITORY NAME] repository, at https://doi.org/[DOI].

2. Data available upon reasonable request:

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

3. Data included within the article:

All data supporting the findings of this study are available within the article and its supplementary information files.

4. Data not publicly available (ethical/legal restrictions):

The datasets are not publicly available due to [reason, e.g., privacy or ethical restrictions], but are available from the corresponding author upon reasonable request.

5. No data generated:

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Recommended Repositories

Authors are encouraged to deposit data in trusted, community-recognized repositories that assign DOIs and support long-term preservation：

Zenodo

General-purpose open repository for all research outputs, free of charge, DOI-assigned.

Figshare

Flexible platform for sharing datasets, figures, code, and supplementary materials.

Dryad

Curated repository for data underlying scientific and medical publications.

Institutional Repositories

University or research institute repositories supporting local open science policies.

Data Citation

Data should be cited in the reference list using the dataset DOI, following standard citation practices. Proper data citation supports academic credit and reproducibility.

Ethics & Privacy

When data involve human participants, authors must ensure compliance with ethical guidelines, informed consent, and data protection laws. Identifiable personal data should be anonymized or shared only under restricted access conditions.

Questions About Data Sharing?

For further guidance on data sharing and data availability statements, contact our editorial office:
Email: [email protected]
Response time: Within 2 business days