PQ encourages authors to maintain the highest levels of transparency and rigor regarding the data that supports their research findings.

Data Availability and Transparency

Research Data Definition: Research data includes the results of observations or experimentation that validate research findings. This can encompass raw data, processed data, software, algorithms, code, models, protocols, and other useful materials related to the project.

Data Sharing Encouragement: Authors are strongly encouraged to deposit their research data in a relevant data repository, such as Mendeley Data, Dryad, Figshare, Open Science Framework, Zenodo, UK Data Service ReShare, OpenICPSR, or Qualitative Data Repository.

These platforms help researchers adhere to FAIR principles (Findable, Accessible, Interoperable, and Reusable). Sharing data promotes the integrity, discovery, and reuse of research, which aids reproducibility and increases research impact. Since PQ employs double-anonymous peer review, authors are strongly recommended to anonymize the authorship in the data provided to reviewers (e.g., via repository links designed to mask identity before public release).

Data Citation and Linking: Authors should cite and link to the dataset in their article if it is deposited in a public repository. Data citations should be included in the reference list and should contain a persistent identifier, such as a Digital Object Identifier (DOI).

Data Availability Statement (DAS): All original research articles should include a Data Availability Statement (DAS). This statement explains how the data supporting the results and analysis in the article can be accessed.

• If data is publicly available, the statement should include links or citations to the archived dataset.
• If data cannot be shared publicly (e.g., due to sensitive or confidential information like human participant privacy), the statement must clearly explain the reason why the data is unavailable or describe the conditions for access.

Retention and Verification: Authors must be prepared to provide the data supporting their paper for editorial review upon request to verify the validity of results. They should also retain such data for a reasonable number of years after publication, and should ideally archive data in perpetuity

Ethical Considerations for Data: If the research involves human participants, authors must confirm that informed consent was obtained, and that all procedures complied with relevant ethical guidelines regarding data protection and privacy rights.

Image Integrity

Authors are required to ensure that all digital images (figures, illustrations, and artwork) accurately represent the original data. Manipulation that could fabricate, falsify, or misrepresent results is considered unethical. Adjustments to brightness, contrast, or color balance are acceptable only if they are applied uniformly across the entire image and do not eliminate or obscure information present in the original. PQ may request the original, unprocessed data files during peer review or post-publication to verify the integrity of figures.