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.

Research 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. All papers, regardless of size, 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