Data Sharing and Reproducability

Data Sharing Policy

Manuscripts must accurately represent research data, with no manipulation, falsification, or omission of relevant findings

Authors are encouraged to make their research data publicly available whenever possible, subject to ethical and legal considerations.

Data Availability Statement

Authors must include a Data Availability Statement in their manuscript, indicating:

    • Whether the data is publicly available.
    • Where and how the data can be accessed (e.g., repository links, supplementary files).
    • Any restrictions or conditions for access.
  1. Data Types
    The journal supports sharing various types of data, including but not limited to:
    • Raw data used in analyses.
    • Processed data.
    • Code, algorithms, and scripts.
    • Protocols and methods.
  2. Data Citation
    All shared data should be cited appropriately in the manuscript and reference list to acknowledge its contribution to the research.     

Reproducibility Policy

  1. Methodological Transparency
    Manuscripts must provide a detailed description of all methods, tools, and techniques used, including:
    • Experimental protocols.
    • Statistical analyses.
    • Software and code versions.
    • Supplementary Information
      Authors should provide any supplementary files necessary to replicate the study like Additional datasets.       

Exceptions and Ethical Considerations

  1. Confidential or Sensitive Data
    Data that includes personally identifiable information or sensitive content must comply with relevant privacy and ethical guidelines. Authors should anonymize data where necessary or explain access restrictions in their Data Availability Statement.
  2. Legal Restrictions
    Data sharing is not mandatory if it conflicts with legal, contractual, or ethical obligations. Authors must clearly explain these limitations.

Editorial Review and Compliance

Editors and reviewers may request access to data during the peer-review process to verify the findings and conclusions. Manuscripts lacking sufficient data transparency may be subject to revision or rejection.