Aims & Scope

DATAMIND (DM) is is an international, open-access journal dedicated to advancing the intersection of data science and artificial intelligence. We publish rigorous, high-impact research that explores how data — in all its forms and scales — drives the development of intelligent systems, computational methods, and knowledge discovery across science, industry, and society.

DM welcomes original research articles, comprehensive reviews, perspectives, and technical communications covering the full spectrum of data-driven AI research. The journal follows a quarterly publication schedule. Manuscript submissions are considered year-round, and accepted papers are assigned to the appropriate issue based on submission date.

Double-blinded Peer Review

Committed to scientific integrity and editorial excellence, DM employs a double-blinded peer-review process and adheres to the highest ethical standards as outlined by COPE. The journal embraces transparency, reproducibility, and accessibility, ensuring that all published content is freely available under an open-access model to maximize dissemination and global impact.

ISSN

• - (Online)