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.