Call for 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 35th 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 2023 will be hosted by the University of Southern California’s Information Sciences Institute (USC/ISI) and will continue the tradition of past SSDBM meetings in providing a stimulating environment to encourage discussion, fellowship and exchange of ideas.

The Proceedings of SSDBM 2023 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. The best papers will be considered for publication in the Distributed and Parallel Databases (DAPD) – An International Journal of Data Science, Engineering, and Management, Springer, ISSN: 0926-8782.

Submission Guidelines

Authors are invited to submit original, unpublished manuscripts. We solicit research papers (long and short), and demo papers. All submissions should be formatted according to the ACM Master Article “sigconf” proceedings template. SSDBM 2023 is single-blind reviewed; authors must include their names and affiliations on the first page. All authors should respect the ACM Policy on Authorship. 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: April 30 at 23:59 AoE (Anywhere on Earth)
• Submission site: EasyChair

Research Papers (long and short)

Long papers are up to 12 pages (including references and appendices), and short papers are up to 4 pages (including references and appendices). The former should be descriptions of complete technical work, while the latter should describe interesting, innovative ideas, which nevertheless require more work to mature, or are vision papers. 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. All papers, regardless of size, will be given an entry in the conference proceedings.

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 an entry in the conference proceedings.

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

For questions regarding the call for papers, contact ssdbm2023@easychair.org.