Call for Posters

The International Conference on Scalable Scientific Data Management 2025 aims to bring together domain experts, data management researchers, practitioners, and developers to present and exchange the latest research findings on concepts, tools, and techniques for scalable scientific data management. While previous editions of SSDBM primarily focused on scientific statistical databases, the 37th edition in 2025 will broaden its scope to encompass all areas of scalable and scientific data management. Reflecting this expanded focus, the conference has been renamed from the International Conference on Scientific and Statistical Database Management to the International Conference on Scalable Scientific Data Management, while retaining the well-known acronym, SSDBM.

The new SSDBM conference will serve as a forum for original research contributions, as well as practical system design, implementation, and evaluation of the latest advances in scalable and scientific data management. The program typically features a single-track format to foster active discussion and includes invited talks, panel sessions, and demonstrations of research prototypes and industrial systems.

SSDBM 2025 will be hosted by The Ohio State University in Columbus, Ohio, from June 23 to June 25, 2025. Continuing the tradition of past SSDBM meetings, SSDBM 2025 will offer a stimulating environment designed to foster discussion, collaboration, and the exchange of ideas on all aspects of scientific and statistical data management research, as well as high-performance data analysis tools and techniques for distributed datasets.

The Proceedings of SSDBM 2025 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. [Acceptance pending]

Topics of Interest

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

Scientific Applications, Workflows and Reproducibility

• Design, implementation, optimization, and reproducibility of scientific workflows
• Platforms and tools for reproducible data science and scientific collaboration
• Application case studies (e.g., astrophysics, climate, energy, sustainability, biomedicine)
• Open data standards and cross-platform compatibility for scientific data
• Cloud computing issues in large-scale data management
• System architectures for scientific data
• HPC applications and scalability challenges in data-intensive scientific fields
• Data ethics, bias in scientific data handling, and privacy in large-scale studies
• Handling data errors, inconsistencies, and outliers in scientific datasets

Data Modeling, Management, and Integration

• FAIR data principles (Findable, Accessible, Interoperable, Reusable)
• Data lifecycle and retention management, provenance data management
• Data integration
• Data storage and management architectures (e.g., distributed file systems, data lakes, high-performance storage)
• Protocols and frameworks for cross-domain data sharing and exchange
• Modeling of scientific data
• Schema evolution
• Information retrieval and text mining
• Indexing and querying scientific data, including spatial, temporal, and streaming data

Big Data Processing and Performance Aspects

• Big data processing frameworks for scientific data
• Scalable architectures and distributed systems for managing large-scale datasets
• Optimization techniques for high-efficiency data storage and retrieval
• Innovations in data compression and encoding for enhanced performance
• Efficient computational techniques for statistical data analysis and modeling
• Methods for ensuring data quality, integrity, and consistency in big data environments
• Smart city applications and services leveraging high-performance data solutions

Machine Learning, Artificial Intelligence, and Visualization

• Database support of machine learning and AI
• Data management for AI applications
• Machine learning and AI for scientific data management
• Visualization and exploration of large datasets
• Security and privacy in scientific data management
• Data storage and compression techniques for machine learning

Streaming and Real-Time Data Processing

• Stream data representation and management
• Stream data analysis (e.g., summarization, statistical analysis, pattern matching, pattern discovery, learning, and prediction)
• Dataflow and parallel processing for complex data workflows
• Distributed systems and devices
• Internet of Things (IoT) data analytics
• Location-aware recommender systems

Posters

There will be a poster session where participants will have the opportunity to present their ongoing research with new problems/solutions; and receive feedback from the community. Accepted posters will also be given a short presentation slot in the conference. Posters will be subject to a very light scope and presentation check. The number of accepted posters is limited by the poster space available. Student Poster Competition: The first author of these submissions has to be a student at the time of submission. One poster will be selected for the best poster.

Submission Guidelines

Authors are invited to submit original, unpublished manuscripts.

• An extended abstract (extended abstracts should not exceed 2 pages and 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 2025 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 generative AI tools and technologies (details on the policy are available at ACM Policy on Authorship.
• If the first author is a student, they should indicate whether they would like to be included in the student poster competition.
• A draft of the proposed poster (organized as one A0-size sheet, in vertical (preferred) or horizontal layout).

Submission site: EasyChair

Posters (extended abstracts) will not be included in the proceedings.

At least one author must register for the Technical Program in order to attend the conference and present the poster. For an accepted poster to be included in the presentation schedule or in the student poster computation, the author has to present it at the conference in person. Otherwise, the paper will be removed from the program and the competition.

Important Dates

• Submission deadline: March 31st, 2025 at 23:59 AoE (Anywhere on Earth)
• Notification: April 14th, 2025