Call for Contributions

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Authors are invited to submit original, unpublished manuscripts.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 2020 is single-blind reviewed; authors must include their names and affiliations on the first page. The submission site is on 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 tend to be descriptions of complete technical work, while the latter tend to be descriptions of interesting, innovative ideas, which nevertheless require more work to mature. The program committee may decide to accept some full papers as short papers. Full 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. Authors may optionally include reproducibility information that allows for automated validation of experimental results (see artifact evaluation criteria). Accepted submissions passing automated validation will earn a prestigious “Results Replicated” Badge in the ACM DL in accordance with ACM’s artifact review and badging policy.

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 also 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