Conference Information
SSDBM 2020: International Conference on Scientific and Statistical Database Management
Submission Date:
2020-03-10 Extended
Notification Date:
Conference Date:
Vienna, Austria
CCF: c   CORE: a   QUALIS: a2   Viewed: 13567   Tracked: 36   Attend: 6

Conference Location
Call For Papers

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. 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. All papers, regardless of size, will be given an entry in the conference proceedings.


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
    Provenance data management
    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
Last updated by Dou Sun in 2020-02-23
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