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Parallel Data Object Creation: Towards Scalable Metadata Management in High-Performance I/O Library
Youjia Li, Robert Latham, Robert Ross, Ankit Agrawal, Alok Choudhary, Wei-Keng Liao
https://arxiv.org/abs/2506.15114

Parallel Data Object Creation: Towards Scalable Metadata Management in High-Performance I/O Library
High-level I/O libraries, such as HDF5 and PnetCDF, are commonly used by large-scale scientific applications to perform I/O tasks in parallel. These I/O libraries store the metadata such as data types and dimensionality along with the raw data in the same files. While these libraries are well-optimized for concurrent access to the raw data, they are designed neither to handle a large number of data objects efficiently nor to create different data objects independently by multiple processes, as …

A Hybrid Heuristic Framework for Resource-Efficient Querying of Scientific Experiments Data
Mayank Patel, Minal Bhise
https://arxiv.org/abs/2506.10422 http…

A Hybrid Heuristic Framework for Resource-Efficient Querying of Scientific Experiments Data
Scientific experiments and modern applications are generating large amounts of data every day. Most organizations utilize In-house servers or Cloud resources to manage application data and workload. The traditional database management system (DBMS) and HTAP systems spend significant time & resources to load the entire dataset into DBMS before starting query execution. On the other hand, in-situ engines may reparse required data multiple times, increasing resource utilization and data processing…

A Terminology for Scientific Workflow Systems
Fr\'ed\'eric Sutera, Tain\~a Coleman, \.Ilkay Altinta\c{s}, Rosa M. Badia, Bartosz Balis, Kyle Chard, Iacopo Colonnelli, Ewa Deelman, Paolo Di Tommaso, Thomas Fahringer, Carole Goble, Shantenu Jha, Daniel S. Katz, Johannes K\"oster, Ulf Leser, Kshitij Mehta, Hilary Oliver, J. -Luc Peterson, Giovanni Pizzi, Lo\"ic Pottier, Ra\"ul Sirvent, Eric Suchyta, Douglas Thain, Sean R. Wilkinson, Justin M. Wozniak, Rafael Ferreir…

A Terminology for Scientific Workflow Systems
The term scientific workflow has evolved over the last two decades to encompass a broad range of compositions of interdependent compute tasks and data movements. It has also become an umbrella term for processing in modern scientific applications. Today, many scientific applications can be considered as workflows made of multiple dependent steps, and hundreds of workflow management systems (WMSs) have been developed to manage and run these workflows. However, no turnkey solution has emerged to …

ChatPD: An LLM-driven Paper-Dataset Networking System
Anjie Xu, Ruiqing Ding, Leye Wang
https://arxiv.org/abs/2505.22349 https://arxi…

ChatPD: An LLM-driven Paper-Dataset Networking System
Scientific research heavily depends on suitable datasets for method validation, but existing academic platforms with dataset management like PapersWithCode suffer from inefficiencies in their manual workflow. To overcome this bottleneck, we present a system, called ChatPD, that utilizes Large Language Models (LLMs) to automate dataset information extraction from academic papers and construct a structured paper-dataset network. Our system consists of three key modules: \textit{paper collection},…