Building on a successful inaugural year, DATAMIND invites submissions, which focus on the foundational and frontier questions at the intersection of database systems and artificial intelligence — an intersection that is rapidly reshaping how both fields define their core problems.

The explosion of large language models, multimodal AI, and real-time inference systems has placed unprecedented demands on data infrastructure. At the same time, advances in database technology — from vector indexing at billion-scale to transactional graph systems to cloud-native lakehouses — are creating new possibilities for how AI systems are built, evaluated, and governed. This issue seeks work that addresses both the opportunities and the open challenges this convergence creates.

Priority Topics for This Issue:

• LLMs and Structured Data: grounding language model outputs in relational and graph knowledge bases; text-to-SQL; schema-aware generation
• AI-Ready Data Infrastructure: database architectures designed for training, fine-tuning, and serving ML models at scale
• Multimodal Data Management: unified storage, retrieval, and indexing across text, image, audio, and structured modalities
• Data-Centric AI: dataset curation, active learning, and label quality as first-class research contributions
• Trustworthy Data Systems: privacy-preserving computation, differential privacy in database queries, fairness in data-driven decision systems
• Emerging Storage Paradigms: neuromorphic data processing, DNA storage, quantum-assisted database operations
• Interdisciplinary Applications: healthcare informatics, financial risk systems, climate data platforms, and scientific databases where the data infrastructure design is central to the research contribution

Submission Deadline: 30 June 2026

Expected Publication: September 2026

Article Types Accepted: Original Research · Systematic Review · Perspective · Technical Communication · Dataset Paper

All submissions undergo double-blind peer review in accordance with COPE guidelines. Articles are published under CC BY 4.0. Authors retain copyright. DATAMIND strongly encourages the open sharing of datasets, code, and experimental configurations alongside accepted manuscripts.

Submit at: https://inatgi.in/index.php/dm/submission/wizard

Author Guidelines: https://inatgi.in/index.php/dm/about/submissions

Enquiries: editorial@datamindjournal.com