Data and Reproducibility

 

The journal encourages responsible data availability and research reproducibility. Authors should provide sufficient information about the research design, data sources, analytical procedures, computational methods, and evaluation processes to enable readers to understand how the reported findings were produced.

Data Availability
  • State whether supporting research data are available.
  • Provide a repository or access information when appropriate.
  • Explain restrictions when data cannot be publicly shared.
  • Protect personal, confidential, proprietary, or sensitive information.
  • Ensure that shared data are accompanied by sufficient documentation.
Computational Reproducibility
  • Describe algorithms and analytical procedures sufficiently.
  • Report important parameters and experimental settings.
  • Identify relevant software, libraries, or computational environments.
  • Describe datasets and preprocessing procedures.
  • Report evaluation metrics and validation procedures.
  • Provide source code or supplementary materials when appropriate and legally permissible.
Transparency

Authors should not omit methodological information that is necessary to understand or evaluate the validity of the reported findings. Where complete reproducibility is not possible because of confidentiality, proprietary restrictions, unavailable historical data, or other legitimate limitations, the relevant limitations should be clearly disclosed.