A Provenance Management System for Research Data Management in High-Performance Computing Systems

Yuta Namiki (), Takeo Hosomi, Hideyuki Tanushi, Akihiro Yamashita and Susumu Date
Additional contact information
Yuta Namiki: NEC Corporation
Takeo Hosomi: NEC Corporation
Hideyuki Tanushi: Cybermedia Center, Osaka University, Joint Research Laboratory for Integrated Infrastructure of High Performance Computing and Data Analysis
Akihiro Yamashita: Cybermedia Center, Osaka University, Joint Research Laboratory for Integrated Infrastructure of High Performance Computing and Data Analysis
Susumu Date: Cybermedia Center, Osaka University, Joint Research Laboratory for Integrated Infrastructure of High Performance Computing and Data Analysis

A chapter in Sustained Simulation Performance 2022, 2024, pp 13-24 from Springer

Abstract: Abstract Research data management (RDM) has become increasingly important recently. High-performance computing (HPC) systems that process large volumes of data face the problem of how to manage the research data produced in their systems. Since the purposes of RDM are to improve the reproducibility of research and the reusability of the research data, collecting and managing the provenance of data produced in HPC systems is essential. In this paper, we introduce the concept of a provenance management system for RDM in HPC systems. We analyze use cases of provenance and the requirements for collecting and managing provenance. We also discuss implementation of the requirements. Finally, we introduce our prototype of the provenance management system.

Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-41073-4_2

Ordering information: This item can be ordered from
http://www.springer.com/9783031410734

DOI: 10.1007/978-3-031-41073-4_2

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().