Conference Information

DaWaK 2026: International Conference on Big Data Analytics and Knowledge Discovery

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Submission Date:
2026-03-15
Notification Date:
2026-05-15
Conference Date:
2026-08-11
Location:
Graz, Austria
Years:
28
CORE: b   QUALIS: b1   Viewed: 44284   Tracked: 6   Attend: 0

Call For Papers

DaWaK 2026 (International Conference on Big Data Analytics and Knowledge Discovery) is a CORE B / QUALIS B1 conference held in Graz, Austria on 2026-08-11. The paper submission deadline is 2026-03-15. Acceptance notifications are sent on 2026-05-15.

Scope DaWaK conference is a high-quality forum for researchers, practitioners and developers in the field of Big Data Analytics, in a broad sense. The objective is to explore, disseminate and exchange knowledge in this field through scientific and industry talks. The conference covers all aspects of DAWAK research and practice, including data lakes, database design (data warehouse design, ER modelling), big data management (tables + text + files), query languages (SQL and beyond), parallel systems technology (Spark, MapReduce, HDFS), theoretical foundations and applications, text and data mining techniques, and deep learning. Topics of Interest The conference will bring together active researchers from the database systems, cloud computing, programming languages and data science communities worldwide. Main topics include: Theoretical models for data storage Integration of databases and neural networks Conceptual model foundations for big data Parallel and scalable data processing Distributed and parallel system architectures Query processing and optimization Semantics for big data Data fabric and data lake architectures Data Pre-processing and data cleaning Polystore and multistore architectures SQL alternatives: NoSQL, NewSQL, JSON Cloud infrastructure; containers, virtualization Metadata for big data frameworks Big data storage and indexing Mobile applications Large-scale AI/ML for Multimodal dataa Data Science workflows Analytics on Large Graphs Large-scale unstructured, semi-structured data Data streams: networking and sensor data Trustworthy AI on Data Lakes, Data Grid and Data Fabric Deep learning on large data sets
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Related Journals

CCFFull NameImpact FactorPublisherISSN
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