Challenges of research data management for high performance computing

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Abstract

This paper targets the challenges of research data management with a focus on High Performance Computing (HPC) and simulation data. Main challenges are discussed: The Big Data qualities of HPC research data, technical data management, organizational and administrative challenges. Emerging from these challenges, requirements for a feasible HPC research data management are derived and an alternative data life cycle is proposed. The requirement analysis includes recommendations which are based on a modified OAIS architecture: To meet the HPC requirements of a scalable system, metadata and data must not be stored together. Metadata keys are defined and organizational actions are recommended. Moreover, this paper contributes by introducing the role of a Scientific Data Manager, who is responsible for the institution’s data management and taking stewardship of the data.

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Schembera, B., & Bönisch, T. (2017). Challenges of research data management for high performance computing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10450 LNCS, pp. 140–151). Springer Verlag. https://doi.org/10.1007/978-3-319-67008-9_12

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