JIECA encourages authors to make the data, code, models, and design files underlying their results available so that findings can be verified and built upon.

• Include a Data Availability Statement in every manuscript, stating where the data can be accessed or why it cannot be shared (e.g. commercial or security restrictions).
• Deposit source code and simulation models in a public repository (e.g. GitHub with a Zenodo DOI) where possible, and cite them in the reference list.
• State software names and versions, hardware specifications, and random seeds for machine-learning experiments.
• Experimental datasets should be provided in open, non-proprietary formats where feasible.