会議情報

EDBT 2026: International Conference on Extending Database Technology

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提出日:
2025-10-08
通知日:
2025-11-27
会議日:
2026-03-24
場所:
Tampere, Finland
年:
29
CCF: b   CORE: a   QUALIS: a2   閲覧: 141292   追跡: 115   出席: 19

論文募集

EDBT 2026 (International Conference on Extending Database Technology) is a CCF B / CORE A / QUALIS A2 conference held in Tampere, Finland on 2026-03-24. The paper submission deadline is 2025-10-08. Acceptance notifications are sent on 2025-11-27.

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
最終更新 Dou Sun

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