The complexity of scientific research calls for dynamic integration of various interconnected scientific instruments for data generation (e.g., experiments, observation, and simulation) and data analysis (e.g., AI/ML, visualization, etc.). The capability of near real-time data processing across interconnected scientific instruments is the foundation of various scientific workflows including both traditional human-in-the-loop workflows and autonomous workflows. This is because analysis results are needed near real-time for providing time-sensitive decision making and steering of experiments. However, as the improvement of scientific instruments leads to the generation of scientific data with unprecedented volumes and modalities, it imposes a huge strain on data processing as data acquisition, sharing, and analysis will be prohibitively expensive with the increase of data volumes. This landscape highlights the growing need for research efforts that focus on optimizing all stages of data processing at extreme scale to enable near real-time processing, including but not limited to acquisition, reduction, management, storage, sharing, and analysis. This international workshop on high-performance data management for collaborative research is a response to such a demand by providing a venue for researchers to present research outcomes, exchange ideas, identify new research directions, and foster new collaborations within the community.
Data reduction methods for scientific data
Methods for diverse data types
Methods with accuracy- and feature-preserving guarantees
Optimal design of data reduction methods
AI4Compression
Data analysis over extreme-scale datasets
Surrogate/reduced-order models
Visualization techniques for near real-time computing
Metrics for reduction quality
Computing on reduced data
Accuracy and performance trade-offs
Reduction and system co-design
Accelerating reduction on emerging hardware
Data management and storage for near real-time computing
Runtime systems for data reduction
State of the practice
Resilient near real-time Computing
NRDPISI-1 will accept full papers in IEEE format following eScience formatting rules (limited to 6 pages excluding references) and extended abstracts (2 pages, except references and appendix). All papers must be original and not simultaneously submitted to another journal or conference.
Submission should be made to https://easychair.org/conferences/?conf=escience2024.
Submitted papers will be evaluated by at least 3 reviewers based on technical merits, with the same review criteria of the eScience main conference (single-blind). Accepted papers from the workshop will be published as part of eScience 2024 proceedings by the IEEE Computer Society Press, USA, and made available online through the IEEE Digital Library.
Full Paper submission deadline: July 29, 2024 (AOE) (August 12, 2024) (AOE)
Author notification: August 12, 2024 August 19, 2024
Camera-ready final submission deadline: August 23, 2024 (AoE)
Remote presentation submission deadline: August 30, 2024 (AoE)
Jieyang Chen, University of Alabama at Birmingham
Jinzhen Wang, University of North Carolina at Charlotte