Call for Demo Papers

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 hosted by the Inria centre at Rennes University and 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.

The Proceedings of SSDBM 2024 will be published by Association of Computing Machinery (ACM) International Conference Proceeding Series (ICPS) and will appear in the ACM Digital Library and many indexing providers.

Submission Guidelines

Authors are invited to submit original, unpublished manuscripts.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 and use of large language models (LLMs). At least one author of each accepted paper or poster must register and plan to attend the conference in-person. Each author registration can be applied to only one accepted submission.

• Submission deadline: (Final Extension) May 20 at 23:59 AoE (Anywhere on Earth)
• Submission site: EasyChair

Demo 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. Demo papers will be given a short presentation slot in the conference and presented in the form of posters. Demo papers will be given an entry in the conference proceedings.

Important note to authors about the new ACM open access publishing model

ACM has introduced a new open access publishing model for the International Conference Proceedings Series (ICPS). Authors based at institutions that are not yet part of the ACM Open program and do not qualify for a waiver will be required to pay an article processing charge (APC) to publish their ICPS article in the ACM Digital Library. To determine whether or not an APC will be applicable to your article, please follow the detailed guidance here: https://www.acm.org/publications/icps/author-guidance.

Further information may be found on the ACM website, as follows:

• Full details of the new ICPS publishing model.
• Full details of the ACM Open program.

Please direct all questions about the new model to icps-info@acm.org.

Topics of Interest

Topics of particular interest include, but are not limited to, the following, as they relate to scientific and statistical data management:

• 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