Research data citation policy
Research data, software code, and other research outputs used in the article or generated during the research must be properly cited in the reference list at the end of the manuscript. Data citations are treated as standard scholarly references and should follow the journal’s reference style.

What must be cited
Authors must cite, where applicable:

• Research datasets underlying the reported results (including processed data, where relevant),
• Software and source code used to generate results (including analysis scripts/workflows),
• Other research outputs such as protocols, models, or materials that are essential to reproduce the work.

How to cite research data
Data and software citations must include, at minimum: creator(s), title, year, repository/publisher, and a persistent identifier (preferably a DOI; alternatively Handle/ARK or another stable PID). If a dataset is versioned, the cited reference must specify the version used.

Examples
Dataset (with DOI):
Author(s). Title of dataset. Repository, Year. DOI

Software/code (with DOI):
Author(s). Title of software (Version). Repository/Publisher, Year. DOI

Dataset (accession number/Handle):
Author(s). Title of dataset. Repository, Year. Persistent identifier (e.g., Handle/Accession No.)

Data Availability Statement and citations
The Data Availability Statement should provide the access link(s) to the data and/or code. When data or code are publicly available, they must be cited both in the Data Availability Statement (as a link) and in the reference list (as a formal citation).

Restrictions
If data cannot be shared publicly due to legal, ethical, confidentiality, or commercial restrictions, authors must still cite the dataset where possible and describe the access conditions in the Data Availability Statement. If a public record cannot be created, authors must clearly state the reasons and provide contact details or an access request procedure where feasible.