DAWAK 2023 : The 25th International Conference on Big Data Analytics and Knowledge Discovery
Conference Series : Data Warehousing and Knowledge Discovery
Call For Papers
C A L L F O R P A P E R S
The 25th International Conference on Big Data Analytics and Knowledge Discovery (DAWAK2023)
28 - 30 August, 2023
Papers submission: https://equinocs.springernature.com/service/DAWAK2023
*** IMPORTANT DATES ***
Paper submission: 7 March 2023
Notification of acceptance: 10 May 2023
Camera-ready copies due: 1 June 2023
Conference days: 28-30 August 2023
*** PUBLICATION ***
All accepted conference papers will be published in a volume of "Lecture Notes in Computer Science" (LNCS) by Springer. LNCS volumes are indexed in the Conference Proceedings Citation Index (CPCI), part of Clarivate Analytics’ Web of Science; Scopus; EI Engineering Index; Google Scholar; DBLP; etc. TOP papers, after further revisions, will be invited for publication in a SPECIAL ISSUE of DATA & KNOWLEDGE ENGINEERING (DKE) titled "Data Engineering, Data Analytics and Data science".
*** 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. 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 extended data warehouses and big data
- Conceptual model foundations for big data
- Modelling diverse big data sources
- Parallel processing
- Parallel DBMS technology
- Distributed system architectures
- Scalability and parallelization using Map-Reduce, Spark, and related systems
- Query languages
- Query processing and optimization
- Semantics for big data intelligence
- Data warehouse and data lake architectures
- Pre-processing and data cleaning
- Integration of data warehousing, OLAP cubes, and data mining
- Polystore and multistore architectures
- NoSQL storage systems
- Cloud infrastructures for big data
- Metadata for big data frameworks
- Big data storage and indexing
- Big data analytics: algorithms, techniques, and systems
- Big data quality and provenance
- Big data search and discovery
- Big data management for mobile applications
- Analytic workflows
- Graph analytics
- 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
- Data visualisation
- Big data application deployment
- Data science products
- Novel applications of text mining for big data
- Machine learning: auto AI, deep learning applications
*** SUBMISSION GUIDELINES ***
Authors are invited to 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 15 pages (including references and appendixes). Full papers are expected to be more mature, contain more theory or present a survey (tutorial style) of some hot or not yet explored topics.
Papers exceeding the page limit or deviating from the formatting requirement are desk rejected.
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 reviewing.
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
*** SUBMISSION PROCEDURE ***
Papers submission will be managed using EquinOCS Springer Nature Conference Proceedings Submission System.
Authors should consult Springer’s authors’ instructions (https://www.springer.com/gp/computer-science/lncs/conference-proceedings...) and use the proceedings templates, either for LaTeX or for Word, for the preparation of their papers.
Once you click on the submission link (https://equinocs.springernature.com/service/DAWAK2023), you will be guided to the EquinOCS Login page, which will be open in your browser. Click on the button “Submit now”. This will guide you directly to the paper submission process. If you already have an account at EquinOCS you will be asked to Login. After Login you will be guided to the start page where you can start with your submission. If you do not have an account at EquinOCS yet, please follow the registration process. Once your Account has been created, an email will be sent to the email you have stated in the registration process. Please follow the instructions in this email to activate your account and start your submission.
Please refer to EquinOCS user guide (https://support.springernature.com/en/support/solutions/articles/6000245...) for more information.
*** ACCEPTED PAPERS ***
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.
*** COMMITTEE ***
Program Committee co-Chairs
- Robert Wrembel, Poznan University of Technology, Poland
- Johann Gamper, Free University of Bozen-Bolzano, Italy
Program committee member please refer to DAWAK2023 Website
For further inquiries, please contact email@example.com