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SSDBM 2024 : 36th International Conference on Scientific and Statistical Database Management

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Conference Series : Statistical and Scientific Database Management
 
Link: https://ssdbm.org/2024/index
 
When Jul 10, 2024 - Jul 12, 2024
Where Rennes, France
Submission Deadline May 8, 2024
Notification Due Jun 5, 2024
Categories    scientific database   data management   data systems   statistical database
 

Call For Papers

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36th International Conference on Scientific and Statistical Database Management
July 10–12, 2024
Rennes, France

https://ssdbm.org/2024/
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The SSDBM international conference brings together scientific domain experts, database researchers, practitioners, and developers for the presentation and exchange of current research results on concepts, tools, and techniques for scientific and statistical database applications. The 36th SSDBM will provide a forum for original research contributions and practical system design, implementation and evaluation. The conference program typically consists of a single track to facilitate discussion, and contains presentations of invited talks, panel sessions, and demonstrations of research prototypes and industrial systems.

SSDBM 2024 will be held in Rennes, France, from July 10th to 12th. SSDBM 2024 will continue the tradition of past SSDBM meetings in providing a stimulating environment to encourage discussion, fellowship and exchange of ideas in all aspects of research related to scientific and statistical data management, and high-performance data analysis tools and techniques for distributed datasets. Topics of interest in SSDBM 2024 papers include, but are not limited to:

- Modeling of scientific data
- Indexing and querying scientific data, including spatial, temporal, and streaming data
- FAIR data principles (Findable, Accessible, Interoperable, Reusable)
- Provenance data management
- Schema evolution
- Data integration
- Visualization and exploration of large datasets
- Spatial, temporal and spatio-temporal scientific data
- Geographical information retrieval
- Location-aware recommender systems
- Stream data representation and management
- Stream data analysis, e.g., summarization, statistical analysis, pattern matching, pattern discovery, learning, and prediction
- Design, implementation, optimization, and reproducibility of scientific workflows
- Security and privacy
- Cloud computing issues in large-scale data management
- Information retrieval and text mining
- System architectures
- Case studies (e.g., astrophysics, climate, energy, sustainability, biomedicine)
- Distributed systems and devices
- Internet of Things data analytics
- Smart city applications and services
- Database support of machine learning and AI


Submission Guidelines
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Authors are invited to submit original, unpublished manuscripts. All submissions should be formatted using the ACM format available at https://www.acm.org/publications/proceedings-template by selecting the generic “sigconf” sample. For submissions prepared in LaTex, authors are recommended to use \documentclass[sigconf,review]{acmart} configuration. SSDBM 2024 is single-blind reviewed; authors must include their names and affiliations on the first page. All authors should respect ACM Policy on Authorship (https://www.acm.org/publications/policies/new-acm-policy-on-authorship) and use of large language models (LLMs). At least one author of each accepted paper (full, short or demo) must register and plan to attend the conference in-person. Each author registration can be applied to only one accepted submission.

Submission site: https://easychair.org/my/conference?conf=ssdbm2024

Full papers are up to 12 pages (including references and appendices). Papers should be descriptions of complete technical work. The program committee may decide to accept some long papers as short papers. Long papers will be given a presentation slot in the conference, while short papers will be presented in the form of posters and given a short presentation slot in the conference.

Short papers are up to 4 pages (including references and appendices). Short papers should describe interesting, innovative ideas, which nevertheless require more work to mature, or are vision papers.

Demo papers are up to 4 pages (including references and appendices). Proposals should provide the motivation for the demonstrated concepts, the information about the technology and the system to be demonstrated (including a system description, functionality and figures when applicable), and should state the significance of the contribution. Selection criteria for the demonstration proposals evaluation include: the novelty, the technical advances and challenges, and the overall practical attractiveness of the demonstrated system.

All papers (Full, Short, and Demo) will appear in the proceedings to be published by Association of Computing Machinery (ACM) International Conference Proceeding Series (ICPS). Accepted papers will also need to follow the conference registration policy to be included in the conference proceedings.

Important Deadlines (AOE)
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- Full paper submission deadline: May 8 2024
- Short paper submission deadline: May 6, 2024
- Demo paper submission deadline: May 6, 2024
- Author notification (full papers): June 5, 2024
- Author notification (short and demo papers): June 10, 2024
- Conference: July 10 - July 12, 2024

Organization Committee
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General Chair
Shadi Ibrahim, Inria, France

General Vice Chair
Suren Byna, The Ohio State University, USA

Program Chairs
Tristan Allard, University of Rennes, France
Jay Lofstead, Sandia National Laboratories (SNL), USA
Amelie Chi Zhou, Hong Kong Baptist University, Hong Kong

Short Paper Chairs
Tassadit Bouadi, University of Rennes, France
Jalil Boukhobza, National Institute of Advanced Technologies of Brittany (ENSTA Bretagne), France

Demo Paper Chairs
Diana Moise, HPE, Switzerland
Cédric Tedeschi, University of Rennes, France

Proceedings Chair
Jean Luca Bez, Lawrence Berkeley National Laboratory, USA

Local Event Coordinator
Edith Blin, Inria, France

Web Chairs
Marc Tranzer, Inria, France
Mohammad Rizk, Inria, France

Steering Committee
Arie Shoshani, Lawrence Berkeley National Lab (Chair Emeritus)
John Wu, Lawrence Berkeley National Lab (Chair)
Michael Böehlen, University of Zurich
Tanu Malik, DePaul University
Xingquan (Hill) Zhu, Florida Atlantic University
Yongluan Zhou, University of Copenhagen

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