Aims & Scope

DATAMIND (DM) is an international, peer-reviewed, open access journal dedicated to advancing scholarly understanding of database-centered artificial intelligence and computational systems. The journal positions the database — in all its structural, relational, and distributed forms — as the foundational substrate from which intelligent computation emerges, and publishes research that examines, extends, and applies this relationship across theory and practice.

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)