#Call for Papers

We invite original submissions on data reduction for big data across high-performance computing, cloud, edge, and IoT platforms, spanning algorithms, mathematics, system software, hardware co-design, and application-driven methods. IWBDR-6 targets IEEE BigData attendees facing data-volume bottlenecks across HPC simulations, AI/ML pipelines, cloud and edge analytics, and experimental facilities, where reduction-specific techniques such as error-bounded lossy compression, progressive reduction, and neural-hybrid encoders are rarely covered in depth.

#Topics of Interest

The research topics covered by IWBDR-6 include, but are not limited to:

Data reduction techniques for big data issues in high-performance computing (HPC), cloud computing, Internet-of-Things (IoT), edge computing, machine learning and deep learning, and other big data areas:

- Lossy and lossless compression methods
- Approximate computation methods
- Compressive/compressed sensing methods
- Reduction methods for unstructured data
- Tensor decomposition methods
- Data deduplication methods
- Domain/motif-specific methods, such as (un)structured meshes, particles, tensors
- Accuracy-guarantee data reduction methods
- Optimal design of data reduction methods
- Progressive data reduction methods
- Methods to provide reduced models/representations

Additional topics of interest:

- Mathematical methods with provable error bounds on data, features, and derived quantities of interest
- Metrics and infrastructures to evaluate reduction methods and assess quality/fidelity of reduced data
- Uncertainty quantification for reduction methods/models/representations
- Benchmark applications and datasets for big data reduction
- Data analysis and visualization techniques leveraging reduced data
- Characterizing the impact of data reduction techniques on applications
- Mitigating artifacts produced by scientific data compressors
- Hardware-software co-design of data reduction
- Trade-offs between accuracy & performance on emerging computing hardware and platforms
- Resource-constrained and/or time-constrained data reduction methods
- Software, tools, and programming models for managing reduced data
- Runtime systems and supports for data reduction
- Development of composable data reduction pipelines/workflows
- Automation of data reduction in scientific workflows
- Data reduction challenges and solutions in observational and experimental environments

# Submission

Full workshop papers are submitted through the IWBDR-6 submission portal. Each paper receives at least three single-blind reviews from the Program Committee. At least one author of every accepted paper must register and present (in person or virtually).

# Important Dates

- Full paper submission deadline: October 30, 2026 (Friday)
- Author notification: November 13, 2026 (Friday)
- Camera-ready deadline: November 20, 2026 (Friday)
- IWBDR-6 workshop: December 14–17, 2026 (the specific date is to be announced)