We invite submissions (1-page abstracts) on a broad range of topics, including but not limited to:
Data storage, indexing, and management: advanced methods for structuring, organizing, and maintaining large and heterogeneous data collections.
Database theory and models: formal foundations of data models, query languages, and semantic representations.
Performance and scalability: algorithms, architectures, and techniques for optimizing database systems under increasing workloads.
Data integration and quality: methodologies for cleaning, reconciling, and enhancing data across diverse sources and ontologies.
Knowledge discovery and learning: approaches to data mining, machine learning, and information retrieval in structured and unstructured settings.
Security, privacy, and personalization: mechanisms for safeguarding data while enabling controlled access and adaptive user experiences.
Big data and data science: principles, platforms, and applications for large-scale data analysis and predictive modeling.
Interdisciplinary intersections: interactions between databases and fields such as artificial intelligence, large language models, distributed systems, and related domains.