TOPICS OF INTEREST

Topics of interest include, but are not limited to:

Data Management Systems

Monitoring, testing, and tuning database systems
Cloud, distributed, decentralized, and parallel data management
Database systems on emerging hardware
Embedded databases, IoT, and Sensor networks
Storage, indexing, and physical database design
Query processing and optimization
Transaction processing
Data warehousing, OLAP, Analytics

Data Models and Languages

Data models and semantics
Declarative programming languages and optimization
Spatial and temporal data management
Graphs, social networks, web data, and semantic web
Multimedia and information retrieval
Data lakes
Uncertain, probabilistic, and approximate databases
Streams and complex event processing

Human-Centric Data Management

Data exploration, visualization, query languages, and user interfaces
User-centric and human-in-the-loop data management
Crowdsourced and collaborative data management

Data Governance, Quality, and Fairness

Data integration, information extraction, and schema matching
Data provenance and workflows
Metadata management
Data security, privacy, and access control
Data quality and data cleaning
Responsible data management and data fairness

Modern AI & Data Management

Structured queries over unstructured data: images, video, natural language, etc.
Natural language queries
Machine learning methods for database engine internals
Machine learning methods for database engineering
Data management and metadata for machine learning pipelines
AI & knowledge bases
Data mining & prescriptive analytics in databases
Systems for AI

Other topics which are not listed but clearly address data management related challenges are also welcome. SIGMOD also welcomes submissions on inter-disciplinary work, as long as there are clear contributions to management of data.