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DC-DB&IS 2022 : Doctoral Consortium of the 15th Baltic DB&IS

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Link: https://dbis2022.lu.lv/programme/doctoral-consortium/
 
When Jul 3, 2022 - Jul 3, 2022
Where Riga, Latvia
Submission Deadline Mar 9, 2022
Notification Due Apr 6, 2022
Final Version Due May 9, 2022
Categories    digital business   intelligent systems   e-governance   information systems
 

Call For Papers

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15th Intl. BALTIC DB&IS 2022
Call for Doctoral Consortium Papers
3 July 2022, Riga, Latvia

https://dbis2022.lu.lv
https://dbis2022.lu.lv/programme/doctoral-consortium/
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The 15th International Baltic Conference on Digital Business and Intelligent Systems is a continuation of the biennial International Baltic conference on Databases and Information Systems (Baltic DB&IS) held since 1994. Inheriting the scope of the previous editions of the conference series, the Baltic DB&IS 2022 conference focuses on the advances of computer science in digital business and intelligent systems and provides a rich environment for exchanging research findings and ideas among scientists, practitioners, and doctoral students from the Baltic Sea region, Europe, and the rest of the world.

The Baltic DB&IS 2022 Doctoral Consortium is intended to bring together doctoral students working on the crucial matters of engineering reliable, secure and sustainable information systems for digital business and intelligent systems. The Doctoral Consortium will provide PhD students an opportunity to:
- Present their research work in a relaxed and supportive environment;
- Discuss their work and receive constructive feedback and advice from leading researchers;
- Network with peers and future colleagues.

IMPORTANT DATES:
Paper submission: 9 March 2022
Notification to authors: 6 April 2022
Doctoral Consortium: 3 July 2022
Conference: 4-6 July 2022

TOPICS:
We welcome original unpublished contributions that have not been reviewed elsewhere and are in line with the main conference topics (see below).

SUBMISSIONS:
We welcome submissions (6-8 pages, Springer LNCS format) solely authored by doctoral students describing their current research. Acknowledgements to the supervisor can be included. The paper must adhere to the following conditions and include:
- Introduction and Motivation, identifying a significant problem in the field and its importance,
- Clear formulation of research question(s),
- State of the Art - describing related work or studies,
- Research Method, i.e., research methodology that is applied or planned,
- Results and their evaluation/validation,
- Conclusions.

PUBLICATIONS:
Accepted Doctoral Consortium papers will be submitted for online publication as CEUR Workshop proceedings (indexed in DBLP).

Authors of the best DC papers (written by a doctoral student) are invited to submit an extended version of their paper to international scholarly Gold open access electronic journal Baltic Journal of Modern Computing (BJMC) (ISSN / E-ISSN: 2255-8950, indexed in SCOPUS and Web of Science. The extended version may be co-authored.

KEYNOTE:
'Data Management Systems: Evolution, State of the Art and Open Issues'
Prof. Dr. Abdelkader Hameurlain
Pyramid Team, Institut de Recherche en Informatique de Toulouse (IRIT), Paul Sabatier University, France


ORGANIZATION:
Doctoral Consortium Co-chairs:
- Tarmo Robal, Tallinn University of Technology, Estonia
- Diana Kalibatienė, Vilnius Gediminas Technical University, Lithuania
- Ģirts Karnītis, University of Latvia, Latvia

VENUE:
The International Baltic DB&IS 2022 conference will take place in Riga, the capital of Latvia, whose picturesque medieval Old Town is known around the world for its well-preserved completeness and authentic Hanseatic architecture.

Conference website: https://dbis2022.lu.lv

Baltic DB&IS 2022 is being prepared as a physical event held in Riga, with support for your virtual participation.
See you in July in Riga!


---------------------------- LIST OF TOPICS ----------------------------
The topics of the contributions include, but are not limited to:

Computer Science Models, Methods, Algorithms, and Tools for Digital Business:
- Digitalization in Enterprise Ecosystems
- Business Process Management, Automation, and Simulation-based Optimization
- Advanced Socio Cyber Physical Systems
- Web Information Systems and Web Engineering
- Digital Humanities and Cultural Heritage
- Digitalization in Healthcare
- Digitalization in Education
- Digitalization in Agriculture and Forestry
- Smart Cities
- Computational Biology
- E-governance and E-commerce

Knowledge and Knowledge Technologies for Digital Business and Intelligent Systems:
- Machine Learning
- Information Retrieval
- Knowledge Graphs, Semantic Web, and Semantic Technologies
- Open Data and Linked Data
- Natural Language Processing
- Perception and Cognitive Systems
- Advanced Knowledge Management
- Research Methods in Computer Science and Information Systems Engineering
- Computational Thinking for STEM and Engineering Education

IT Support for Digital Transformation:
- Approaches for Digital Transformation
- Requirements Engineering for Digital Transformation
- Software and Data Quality Systems
- Advanced Computer Networks
- Risk and Security Management and Fraud Detection
- Recommender Systems

Artificial Agents and Smart Systems for Digital Business:
- Artificial Agents and Human-computer Interaction
- Artificial Intelligence and Machine Vision
- Intelligent Methods for Cybersecurity, Robotics, and Smart Industrial Systems
- Intelligent Platforms and Infrastructures for Digital Business
- Evidence Based Systems

Data, Data Science, and Computing for Digital Business and Intelligent Systems:
- Computational Modeling
- Algorithms and Software for Quantum Computers
- Knowledge-based Computing
- Uncertainty Handling in Computing
- Data Storage, Mining, and Analytics
- Big Data, Temporal Data, Geospatial Data

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