Conference Information
ICDT 2021: International Conference on Database Theory
https://edbticdt2021.cs.ucy.ac.cy/
Submission Date:
2020-09-21
Notification Date:
2020-11-27
Conference Date:
2021-03-23
Location:
Nicosia, Cyprus
Years:
24
CCF: b   CORE: a   QUALIS: b1   Viewed: 18913   Tracked: 55   Attend: 7

Conference Location
Call For Papers
ICDT is an international conferences series that addresses the principles and theory of data management. Since 2009, it is annually and jointly held with EDBT, the international conference on extending database technology.
See also https://databasetheory.org/icdt-pages 

Broadening Scope

As ICDT strives to broaden its scope, ICDT 2021 will continue to have a Reach Out Track that calls for

– novel formal frameworks or directions for database theory and/or
– connections between principles of data management and other communities.

The aim of the Reach Out track is to present novel and important directions for database theory and to expand the scope and impact of ICDT towards neighboring communities such as Database Systems, Artificial Intelligence, Knowledge Representation, Machine Learning, Programming Languages, Distributed Computing, and Operating Systems. It is reasonable for articles submitted to this track to be be shorter than regular ICDT submissions. Submissions will be judged mainly in terms of their potential to lead to valuable and impactful theoretical developments. We encourage authors to illustrate the potential impact via convincing examples, preliminary results, and clearly specified open problems. However, the Program Committee reserves the right to re-classify a Reach Out paper submission as a regular submission.

Topics of Interest

Every topic related to the principles of data management is relevant to ICDT. Particularly welcome are contributions that connect data management to theoretical computer science, and those that connect database theory and database practice.

Examples of relevant topics include:
– Data mining, information extraction, information retrieval, and database aspects of machine learning
– Data models, design, structures, semantics, query languages, and algorithms for data management
– Distributed and parallel databases, cloud computing
– Databases and knowledge representation
– Graph databases, (semantic) Web data, and Web services
– Data streams and sketching
– Data-centric (business) process management and workflows
– Data and knowledge integration and exchange, data provenance, views, and data warehouses
– Domain-specific databases (multimedia, scientific, spatial, etc)
– Data privacy and security, concurrency, and recovery
Last updated by Dou Sun in 2020-09-03
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