Research datasets

Imafronte, in line with its commitment to advancing Open Science, firmly supports the practice of depositing research datasets. This policy aligns with current international initiatives, mandates, and guidelines that emphasize both the intrinsic value of scientific data and the necessity of ensuring their accessibility, sharing, and reuse. Consequently, any institutional action aimed at facilitating these processes acquires a strategic and essential character for the advancement of knowledge.

The journal strongly recommends that the datasets underlying accepted articles be deposited in reputable and accredited repositories, preferably those specialized in the relevant discipline. Nevertheless, the use of generalist repositories is also accepted, provided they meet the required quality standards. In all cases, it is imperative that the selected repository complies with the FAIR principles (Findable, Accessible, Interoperable, Reusable), ensuring that datasets are easily located, openly accessible, and interoperable without restrictions, thereby promoting their reuse by the scientific community.

At present, there exists a wide array of repositories specifically designed for the preservation and dissemination of diverse data types, including survey results, interviews, observations, simulations, automatically collected data, samples, models, among others. In this regard, Imafronte has established a dedicated section within the institutional repository of the University of Murcia (DIGITUM), intended for the publication, preservation, and dissemination of datasets linked to published articles. Authors are required to provide these datasets so that the editorial committee may proceed with their deposit in this repository prior to the article’s publication, without precluding the possibility of simultaneously archiving the files in other repositories deemed appropriate by the researchers.

Additionally, the Library of the University of Murcia has developed a detailed guide to assist authors in the correct preparation, documentation, and publication of their datasets. Consulting and adhering to this guide is mandatory during the preparation process and constitutes a prerequisite for manuscript evaluation. Authors must submit the datasets alongside the original manuscript, enabling the editorial team to review them in accordance with the journal’s established criteria.

This policy seeks to strengthen the transparency, reproducibility, and dissemination of scientific knowledge, fostering a more open, accessible, and collaborative academic ecosystem.