Research Data and Reproducibility

The journal supports transparency, reproducibility, and responsible management of scientific data.

Authors conducting experimental, computational, simulation-based, data-driven, artificial-intelligence, or engineering research are encouraged to provide a Data Availability Statement.

Where ethically and legally possible, supporting research materials should be made available through an appropriate repository.

Supporting materials may include:

• datasets;
• source code;
• algorithms;
• model configurations;
• trained model information;
• simulation parameters;
• experimental protocols;
• technical drawings;
• calibration information;
• statistical code;
• supplementary figures; and
• other materials necessary for verification or reproduction.

For machine-learning research, authors should report sufficient information regarding data sources, preprocessing, training, validation, evaluation metrics, baseline comparisons, and model limitations.

Data should not be publicly released where disclosure would violate privacy, security, intellectual-property rights, commercial confidentiality, contractual restrictions, or applicable laws.

Related Policies:
Ethical Oversight | Author Guidelines | Artificial Intelligence Policy