TOPICS

We invite submissions in the following topics:

Data Management Systems

    Benchmarking, 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

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
    Uncertain, probabilistic, and approximate databases
    Streams and complex event processing

Human-Centric Data Management

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

Data Governance

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

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 tuning
    Data management and metadata for machine learning pipelines
    Knowledge base management
    Data mining
    Prescriptive Analytics

Data-Driven Applications

    Data-intensive (DI) applications
    Data Science (DS) pipelines
    Note that submissions in this topic should:
        Focus on data life cycle and pipelines in DS applications OR novel data management in DI fields outside our core (e.g., graphics, networking, astronomy).
        Detail deployed solutions for DS or DI applications.
        Share real-world experiences.
        Provide access to systems, datasets, query logs, benchmarks.
        Describe the impact of the contribution on future research.