The annual International Conference on Extending Database Technology (EDBT) is a leading international forum for researchers, developers, and users to present and discuss cutting-edge ideas, and to exchange techniques, tools and experiences related to data management.

The conference invites submissions of original research contributions related to all aspects of data management. We particularly encourage submissions that focus on the following themes:

    The design and use of novel data science systems
    Synergies between database theory and database systems
    Synergies between data management and HCI
    Synergies between data management and machine learning
    Synergies between data management and modern hardware
    Ethical, social, and legal issues of database technology

A list of specific topics of interest is provided below and is by no means exhaustive:

    Availability, reliability, and scalability
    Benchmarking and performance evaluation
    Big data storage, processing, and transformation
    Cloud data management
    Complex event processing and data streams
    Concurrency control, recovery, and transaction management
    Crowdsourced and collaborative data management
    Data economy, data markets
    Data integration, heterogeneous data management, and schema integration
    Data intensive and data driven systems for ML/AI
    Data management and analytics for semantic web and social networks
    Data mining and knowledge discovery
    Data models and semantics
    Data platforms for modern hardware, and modern hardware for data platforms
    Data quality, curation, and provenance
    Data sovereignty, privacy, security, and access control
    Data system benchmarking, tuning, monitoring, and performance evaluation
    Data visualization, exploration and user interfaces
    Data warehousing, large-scale analytics, and ETL tools
    Distributed and parallel data management, distributed ledgers, and blockchains
    Graph data management
    Green data management
    Human-data interaction
    Knowledge graphs and knowledge management
    Machine learning methods for data and database tuning
    Metadata management and standards
    Middleware and workflow management
    Natural language processing for databases
    Query processing and optimization techniques
    Querying of unstructured and multimedia datasets
    Responsible data management and ethics
    Scientific and statistical data management
    Semi-structured data management
    Sensor, IoT, and mobile data management
    Spatial, temporal, and geographic data management
    Storage, indexing, and physical database design
    Text data management and information retrieval
    Uncertain, probabilistic, and approximate data management
    Usability, automaticity, interpretability, and explainability of data systems