**** PUBLICATION ****
All accepted conference papers will be published in a volume of "Lecture Notes in Computer Science" (LNCS) by Springer. All published papers will be indexed appropriately in all major indexes. Selected high-quality papers, after revision and extension,  will be invited to be published, 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 Systems
- 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

**** SUBMISSION GUIDELINES ****
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 equirements may be rejected without review. The submitted manuscript should closely reflect the final paper as it will appear in the Proceedings.

    Formatting guidelines: http://www.dexa.org/formatting_guidelines
    Online Papers Submission: https://easychair.org/conferences/?conf=dawak2021

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.

**** ACCEPTED PAPERS ****
All accepted conference papers (including the short ones) will be published in a volume of "Lecture Notes in Computer Science" (LNCS) by Springer Verlag. Selected high-quality papers, after revision and extension,  will be invited to be published, in a special issue of Data & Knowledge Engineering (DKE)

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.