Advanced Database Systems
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 30 May 2026 | Viewed by 23
Special Issue Editors
Interests: database; big data; data lake; data engineering; models
Interests: database theory; database integrity; data warehouses; data cleaning; compact data structures; database; data warehouse; data processing
Interests: deep learning and big data; biometric recognition; information security; cloud and fault computing; multimedia applications; medical applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Modern database systems face increasing challenges due to the volume, variety, and velocity with which data is generated and consumed in different domains of knowledge and industry. The evolution of cloud computing, artificial intelligence, data science, and the Internet of Things (IoT) has driven a profound transformation in how data is stored, managed, and used. These advances require more robust, scalable, and adaptable systems that respond to technical and organizational needs.
This Special Issue aims to bring together original research and high-quality reviews that address current challenges in designing, implementing, and evaluating advanced database systems. Papers that propose new data governance models, strategies for collaborative team management, innovative repository architectures, adaptive techniques for specific contexts (such as geospatial or biomedical databases), and efficient algorithms for information processing and retrieval will be especially valued.
We also encourage case studies that show the practical application of emerging technologies, tools to ensure data quality and integrity, or interdisciplinary approaches that combine engineering, computer science, and data management.
Suggested topics include the following:
Advanced Database Systems Design and Evaluation.
Data governance and data quality.
Distributed systems and cloud databases.
Big data storage and retrieval.
NoSQL, NewSQL, and multi-model databases.
Collaborative management and administration of DB development teams.
Data modeling and specialized repository design.
Data processing algorithms and query optimization.
Emerging technologies in data management.
Adaptive and contextual databases
Dr. Ania Cravero
Dr. Mónica Caniupan
Prof. Dr. Shi-Jinn Horng
Guest Editors
Manuscript Submission Information
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Keywords
- database
- data governance
- data quality
- database type
- data modeling
- data repositories
- query optimization
- data processing algorithms
- adaptive database systems
- team management in database projects
- metadata and schema evolution
- data integration
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