Conference Information
VLDB 2025: International Conference on Very Large Data Bases
https://vldb.org/2025/
Submission Date:
2025-03-01
Notification Date:
2025-04-15
Conference Date:
2025-08-28
Location:
London, UK
Years:
51
CCF: a   CORE: a*   Viewed: 120167   Tracked: 231   Attend: 23

Call For Papers
PVLDB welcomes original research papers on a broad range of topics related to all aspects of data management. The themes and topics listed below are intended to serve primarily as indicators of the kinds of data-centric subjects that are of interest to PVLDB – they do not represent an exhaustive list.

Data Mining and Analytics
∟ Data warehousing, OLAP
∟ Parallel and distributed data mining
∟ Data stream mining
∟ Mining/analysis of different data types (e.g., scientific/business, social networks, text, web, graphs, rules, patterns, logs, time series, spatio-temporal)
∟ Explainable AI

Data Privacy and Security
∟ Access control and privacy
∟ Blockchain

Database Engines
∟ Access methods
∟ Concurrency control, recovery, and transactions
∟ Memory and storage management
∟ Multi-core processing and hardware acceleration
∟ Query processing and optimization
∟ Views, indexing, and search

Database Performance and Manageability
∟ Administration and manageability
∟ Tuning, benchmarking, and performance measurement

Distributed Database Systems
∟ Cloud data management, resource management, database as a service
∟ Data networking and content delivery
∟ Distributed analytics
∟ Distributed transactions

Graph and Network Data
∟ Graph data management
∟ Hierarchical, non-relational, and other modern data models
∟ Social networks

Information Integration and Data Quality
∟ Data cleaning, data preparation
∟ Heterogeneous and federated DBMS, metadata management
∟ Knowledge graphs and knowledge management
∟ Schema matching, data integration
∟ Source discovery
∟ Web data management and Semantic Web

Languages
∟ Data models and query languages
∟ Schema management and design

Machine Learning, AI, and Databases
∟ Applied ML and AI for data management
∟ Data management issues and support for ML and AI

Novel Database Architectures
∟ Data management on novel hardware
∟ Embedded and mobile databases
∟ Energy-efficient data systems
∟ Real-time databases, sensors and IoT, stream databases
∟ Video management and analytics systems
∟ Vector databases
∟ Time series databases

Provenance and Workflows
∟ Debugging
∟ Process mining
∟ Profile-based and context-aware data management
∟ Provenance analytics

Specialized and Domain-Specific Data Management
∟ Crowdsourcing
∟ Ethical data management
∟ Fuzzy, probabilistic, and approximate data
∟ Image and multimedia databases
∟ Scientific and medical data management
∟ Spatial and temporal databases
∟ Time series data
∟ High-dimensional vector data

Text and Semi-Structured Data
∟ Data extraction
∟ Information retrieval
∟ Semi-structured data management, RDF
∟ Text in databases

User Interfaces
∟ Data exploration tools
∟ Database support for visual analytics
∟ Database usability
∟ Explainable AI
∟ Interactive querying and visualization for large data
∟ NL interfaces to data
∟ Recommender engines
Last updated by Dou Sun in 2024-05-12
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