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IWBDR 2023 : The Fourth International Workshop on Big Data Reduction


When Dec 15, 2023 - Dec 18, 2023
Where Sorrento, Italy & Virtual
Submission Deadline Oct 1, 2023
Notification Due Nov 1, 2023
Final Version Due Nov 20, 2023
Categories    big data   scientific data   data reduction   high-performance computing

Call For Papers

IWBDR 2023 is organized in conjunction with IEEE BigData 2023

The Call for Papers for IWBDR 2023 is now open, with a submission deadline of October 1, 2023 (AoE). IWBDR is a prestigious workshop in big data reduction and analysis. The goal of this workshop is to provide a focused venue for researchers in all aspects of data reduction in all related communities to present their research results, exchange ideas, identify new research directions, and foster new collaborations within the community.

Topics of Interest

The focus areas for this workshop 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
* Tensor decomposition methods
* Data deduplication methods
* Domain-specific methods, e.g., structured/unstructured meshes, particles, tensors
* Accuracy-guarantee data reduction methods
* Optimal design of data reduction methods
* Data reduction challenges and solutions in observational and experimental environments
* Mathematical methods with robustly estimable or provable error bounds for both data and 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
* Hardware-software co-design of data reduction
* Trade-offs between accuracy and 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


All papers accepted for this workshop will be published in the Workshop Proceedings of IEEE Big Data Conference, made available in the IEEE eXplore digital library.

Submission Instructions

Submissions are required to be within 6 pages for short paper or 10 pages for full paper (including references).
Submission link:

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