|
| |||||||||||||
SSDBM 2026 : Scalable Scientific Data Management | |||||||||||||
| Link: https://ssdbm.org/2026/ | |||||||||||||
| |||||||||||||
Call For Papers | |||||||||||||
|
Call for Papers
SSDBM 2026 — 38th International Conference on Scalable Scientific Data Management https://ssdbm.org/2026/ We solicit paper submissions to SSDBM 2026 of high-quality original work that advances the state of the art in scalable scientific data management and closely related fields (see below). Important Dates (all AoE) Abstract submission: April 24, 2026 Paper submission: May 1, 2026 Notification: June 14, 2026 Conference: August 11–13, 2026 in San Diego, CA (USA) The following link has the full topic list, submission guidelines (ACM sigconf format, single-blind review), and the submission site: https://ssdbm.org/2026/callpaper.html Please note that the conference is in-person and that at least one author of each accepted paper must register and present the work. General Scope of Interest SSDBM has evolved from its origins as the International Conference on Scientific and Statistical Database Management into a premier venue for research at the intersection of data systems, scientific applications, and scalable computing, while retaining its well-recognized acronym. The 38th edition continues to broaden its scope across all aspects of scalable and data-intensive scientific computing, hosted by the San Diego Supercomputer Center at UC San Diego. Area 1: Scientific Applications, Workflows, and Reproducibility Area 2: Data Modeling, Management, and Integration Area 3: Big Data Processing and Performance Area 4: Machine Learning, AI, and Visualization Area 5: Streaming and Real-Time Data Processing Area 6: Emerging Directions in Scientific Data Systems (digital twins, autonomous data systems, cross-layer observability, multi-modal analytics) Contact General Chairs Jay Lofstead, Sandia National Laboratories Christine Kirkpatrick, San Diego Supercomputer Center, UC San Diego Program Co-Chairs Hari Devarajan, Lawrence Livermore National Laboratory Diana Moise, Hewlett Packard Enterprise |
|