Lossy Compression of Scientific Data
A special issue of Data (ISSN 2306-5729).
Deadline for manuscript submissions: 31 May 2026 | Viewed by 17
Special Issue Editors
Interests: data compression; scientific data management; high-performance computing; AI for science
Special Issue Information
Dear Colleagues,
The volume of data from modern supercomputing has reached the extent of petabytes and exabytes, raising an urgent need for effective data compression techniques for large-scale scientific data. This Special Issue aims at collecting and presenting in-depth analyses and novel methods of lossy scientific data compression in order to push forward the cutting edge of scientific data management and compression. More specifically, this Special Issue welcomes high-quality original research papers and systematic reviews discussing the current status of scientific lossy compression, new algorithmic designs of scientific lossy compression, and optimization of scientific lossy compression integration into real-world scientific computing workflows. The topics of interest include, but are not limited to, the following:
- Numerical algorithms for scientific lossy compression.
- Data prediction and/or transform techniques for scientific lossy compression.
- Error artifact detection and mitigation in scientific lossy compression.
- Deep-learning-based scientific lossy compression.
- QoI/RoI integration into scientific lossy compression.
- Scientific lossy compression for unstructured data/particle data.
- Homomorphic scientific lossy compression.
- Parallel/GPU-based scientific lossy compression.
- Compression task scheduling in scientific computing systems.
- Applications of scientific lossy compression.
- Requirement-driven scientific lossy compression.
- Parameter search and/or optimization for scientific lossy compression.
- Lossless coding for scientific lossy compression.
We look forward to receiving your contributions.
Dr. Jinyang Liu
Dr. Sian Jin
Guest Editors
Manuscript Submission Information
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Keywords
- scientific computing
- high-performance computing
- scientific compression
- data compression
- parallel computing
- optimization methods
- numerical algorithms
- numerical analysis
- data coding
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