DaWaK 2019 : 21st International Conference on Big Data Analytics and Knowledge Discovery

  in Conferences   Posted on February 3, 2019

Conference Information

Submission Deadline Monday 18 Mar 2019
Conference & Submission Link http://www.dexa.org/dawak2019
Conference Dates Aug 26, 2019 - Aug 29, 2019
Conference Address Linz, Austria
Proceedings indexed by
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Call for Papers

The annual 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 (schema-free repositories), database design (data warehouse design, ER modeling), big data management (tables + text + files), query languages (SQL and beyond), parallel systems technology (Spark, MapReduce, HDFS), theoretical foundations and applications, bringing together active researchers from the database systems, cloud computing, programming languages and data science communities worldwide.

The annual 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 (schema-free repositories), database design (data warehouse design, ER modeling), big data management (tables + text + files), query languages (SQL and beyond), parallel systems technology (Spark, MapReduce, HDFS), theoretical foundations and applications, bringing together active researchers from the database systems, cloud computing, programming languages and data science communities worldwide.

Theoretical Models for Extended Data Warehouses and Big Data

Parallel Processing

Parallel DBMS technology

Schema-free data repositories

Modeling diverse big data sources (e.g. text)

Conceptual Model Foundations for Big Data

Query Languages

Query processing and Optimization

Cost Models for advanced optimization

Semantics for Big Data Intelligence

Data warehouses, data lakes

Big Data Storage and Indexing

Big Data Analytics: algorithms, techniques, and systems

Big Data Quality and Provenance Control

Distributed system architectures

Exploiting hardware to accelerate processing: multicore CPUs, cache memory, GPUs

Cloud Infrastructure to manage big data

Scalability and Parallelization using MapReduce, Spark and related systems

Graph analytics, including social networks and the Internet

Visualization

Big Data Search and Discovery

Big Data Management for Mobile Applications

Analytics for Unstructured, Semi-structured, and Structured Data

Analytics for Temporal, Spatial, Spatio-temporal, and Mobile Data

Analytics for Data Streams and Sensor Data

Analytics for Big Multimedia Data

Real-time/Right-time and Event-based Analytics

Privacy and Security in Analytics

Big Data Application Deployment

Pre-processing and data cleaning to build analytic data sets

Integration of Data Warehousing, OLAP Cubes and Data Mining

Analytic workflows

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