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.