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