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DaWaK 2021 : The 23rd International Conference on Big Data Analytics and Knowledge Discovery


Conference Series : Data Warehousing and Knowledge Discovery
When Sep 27, 2021 - Sep 30, 2021
Where Linz, Austria (Virtual)
Submission Deadline May 2, 2021
Notification Due Jun 1, 2021
Final Version Due Jun 22, 2021
Categories    database   big data   analytics   machine learning

Call For Papers

All accepted conference papers will be published in a volume of
"Lecture Notes in Computer Science" (LNCS) by Springer.

Selected high-quality papers will be invited to be published, after revision
and extension, in a special issue of Data & Knowledge Engineering (DKE).

**** SCOPE ****
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 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. The conference will bring
together active researchers from the database systems, cloud computing,
programming languages and data science communities worldwide.

The list of main topics include:
- Theoretical Models for Extended Data Warehouses and Big Data
- Parallel Processing
- Parallel DBMS Technology
- Schema-free Data Repositories
- Modelling diverse big data sources (e.g. text)
- Conceptual Model Foundations for Big Data
- Query Languages
- Query processing and 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
- Metadata for Big Data Framework
- Polystore and Multistore in Big Data and NoSQL DBMS
- Distributed System Architectures
- Cloud Infrastructure for Big Data
- Scalability and Parallelization using MapReduce, Spark and Related
- Graph Analytics
- 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
- Real-time/Right-time and Event-based Analytics
- Privacy and Security in Analytics
- Big Data Application Deployment
- Pre-processing and Data Cleaning
- Integration of Data Warehousing, OLAP Cubes and Data Mining
- Analytic Workflows
- Novel Applications of Text Mining to Big Data
- Deep Learning Applications
- Data Science Products

Authors are invited to electronically submit original research
contributions or experience reports in English. DaWak will accept
submissions of both short and full papers.

- Short papers: up to 6 pages on preliminary work, vision papers or
industrial applications
- Full papers: up to 12 pages and papers are expected to be more mature,
contain more theory or present a survey (tutorial style) of some
interesting topic.

Any submission that significantly exceeds length limits or deviates from
formatting requirements may be rejected without review. The submitted
manuscript should closely reflect the final paper as it will appear in
the Proceedings.

Formatting guidelines:

Online Papers Submission:

Submitted papers will be carefully evaluated based on originality,
significance, technical soundness, and clarity of exposition.
Duplicate submissions are not allowed and will be rejected immediately
without further review.
Authors are expected to agree to the following terms: "I understand that
the submission must not overlap substantially with any other paper that
I am a co-author of or that is currently submitted elsewhere.
Furthermore, previously published papers with any overlap are cited
prominently in this submission."
Questions about this policy or how it applies to a specific paper should
be directed to the PC Co-chairs.

Authors of selected papers presented at the conference will be invited
to submit extended versions of their papers for publication in:
Data & Knowledge Engineering (DKE) Elsevier

All accepted conference papers (including the short ones) will be published
in a volume of "Lecture Notes in Computer Science" (LNCS) by Springer Verlag.

All published papers will be indexed appropriately in all major indexes.
Authors of all accepted papers must sign a Springer copyright release form.
Papers are accepted with the understanding that at least one author will
register for the conference to present the paper.

Authors of selected papers presented at the conference will be invited to
submit extended versions of their papers for publication in
Data & Knowledge Engineering (DKE) Elsevier. The submitted extended versions
will undergo a further review process. Both full and short papers have the
opportunity to be invited for journal submission, based on the quality of
the presentation at the conference.

**** Conference Chair ****
Matteo Golfarelli, University of Bologna, Italy
Robert Wrembel, Poznan University of Technology, Poland

**** Program Committee ****

For further inquiries, please contact

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