Conference Information
VLDB 2023: International Conference on Very Large Data Bases
Submission Date:
Notification Date:
Conference Date:
Vancouver, British Columbia, Canada
CCF: a   CORE: a*   Viewed: 104503   Tracked: 218   Attend: 19

Call For Papers
Topics of Interest

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  
∟ Mining/analysis of different types of data (e.g., scientific/business, social networks, streams, text, web, graphs, rules, patterns, logs, and spatio-temporal)  

Data Privacy and Security   

∟ Access control and privacy  
∟ Blockchain  

Database Engines   

∟ Access methods  
∟ Currency 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  


∟ 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  

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  

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 2022-05-15
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