1st Workshop on Reliable Large-scale Data Management (RLDM’25)

Call For Papers

As we move into a new era of exponential data growth and rising AI-driven demands, the reliable management of large-scale datasets has become one of the most pressing challenges in distributed systems.

With distributed systems now operating at global scales and underpinning essential services and infrastructures, it becomes essential to tackle emerging data consistency, fault tolerance, storage architectures, and adaptive processing issues. Data-centric workloads from AI, IoT, and other modern applications demand efficient management of structured and unstructured data, seamless interoperability with heterogeneous infrastructures (e.g., cloud, HPC), and support for diverse hardware and technologies (e.g., NVMe, CXL, high-end GPUs). To meet these demands, systems must deliver high-throughput data storage, transfer, and analysis at scale without sacrificing performance. Equally important are reproducibility and data traceability capabilities, robust security and privacy enforcement, and deep observability of system behavior.

The RLDM workshop aims to unite experts and practitioners from academia and industry to share recent developments, explore cutting-edge trends, and foster discussion on scientific and technical advances in the reliable management of ever-growing data volumes. We particularly encourage submissions that propose novel solutions, report experimental results, or present early ideas to shape the future of data-driven distributed systems.

Topics of Interest

Topics of interest include, but are not limited to:

• Storage systems for large-scale scenarios, including distributed databases, file systems, key-value stores, and object storage platforms.
• Reliability and consistency in large-scale data management, covering aspects such as fault tolerance, data recovery, and crash consistency.
• Protocols, methodologies, and tools for efficient and scalable data management.
• Monitoring, tracing, and debugging techniques for data-intensive and distributed applications.
• Data security, privacy, governance, and regulatory compliance in diverse and heterogeneous environments.
• Optimizations for large-scale data management, including caching, tiering, prefetching, compression, and deduplication.
• Peer-to-peer systems and large-scale collaborative platforms that facilitate decentralized interaction and data sharing.
• Data management systems to support AI workloads, addressing the specific needs of AI pipelines and datasets.
• AI-driven approaches for enhancing data management, including auto-configurable storage, adaptive solutions, and intelligent resource allocation.
• Emerging hardware and cutting-edge technologies for data management, including Compute Express Link (CXL), persistent memory, and resource disaggregation.

Type of Submissions

We welcome submissions from both academia and industry in the following categories:

• Research Papers (up to 6 pages, including references): Original, unpublished work that may include novel research contributions, system architectures, experimental results, or work in progress with initial validation.
• Fast Abstracts (up to 2 pages, excluding references): Early-stage research, position papers, or preliminary ideas and findings, intended to stimulate discussion and receive early feedback from the community.

Submission Guidelines

All papers must be written in English and submitted as a single PDF file via the EasyChair system, following the IEEE double-column format. Submissions can either be Research Papers (6 pages, including references) or Fast Abstracts (2 pages, excluding references). The first page must clearly state the submission type, either Research Paper or Fast Abstract, and indicate if the submission involves industry authors to ensure appropriate reviewer assignment.

Submission Site: https://easychair.org/conferences/?conf=rldm25

Review Process: All submissions will undergo double-blind peer review by the workshop Program Committee, evaluating quality, originality, and relevance. Papers that do not comply with anonymization or formatting guidelines (e.g., page limits) or that have been previously published will be desk-rejected without review.

Presentation and Publication: At least one author of each accepted paper must register and present their work at the workshop. Accepted Research Papers are eligible for inclusion in the SRDS 2025 proceedings (optional), which requires full registration at SRDS. Fast Abstracts will not be included in the published proceedings.

Important Dates

(All deadlines are at 23:59 AOE)

• Paper Submission Deadline: July 4, 2025
• Author Notification: July 25, 2025
• Camera-ready Deadline: July 31, 2025
• Workshop Date: September 29, 2025

Committees

Workshop Chairs

• Francisco Cruz – InvisibleLab, Portugal
• Francisco Maia – Universidade do Porto, Portugal
• Tânia Esteves – INESC TEC, Portugal

Program Committee

• Amit Ruhela – TACC, USA
• Cláudia Brito – INESC TEC & University of Minho, Portugal
• Davy Preuveneers – KU Leuven, Belgium
• Edgar Martinez – AIST, Japan
• Miguel Matos – IST Lisbon & INESC ID, Portugal
• Nuno Machado – Amazon, Spain
• Peterson Yuhala – University of Neuchâtel, Switzerland
• Ricardo Macedo – INESC TEC & University of Minho, Portugal
• Ricardo Vilaça – Critical TechWorks & INESC TEC, Portugal
• Rogério Pontes – AutoScout24, Germany
• Stella Bitchebe – McGill University, Canada
• Vera Rimmer –  KU Leuven, Belgium
• Vinicius V. Cogo – LASIGE & University of Lisbon, Portugal
• Vitor Enes – Ditto, Portugal

Contacts

Website: https://rldm.invisiblelab.dev/

For further information, please contact the Workshop Chairs: rldm@invisiblelab.dev.