SC22 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Workshops Archive

RECUP: A (Meta)data Framework for Reproducing Hybrid Workflows with FAIR


Workshop: The 17th Workshop on Workflows in Support of Large-Scale Science (WORKS22)

Authors: Line Pouchard (Brookhaven National Laboratory), Tanzima Islam (Texas State University), and Bogdan Nicolae and Rob Ross (Argonne National Laboratory (ANL))


Abstract: This abstract presents a conceptual framework and methods to extract and share (meta)data (data and metadata) necessary for reproducibility in the context of complex hybrid workflows (workflows that include numerical simulations and data-intensive applications) executed at extreme scale. We target Digital Objects required to reproduce results and performance: we capture, fuse, and analyze (meta)data to select parameters influencing reproducibility, and make them FAIR Digital Objects for re-use.





Back to The 17th Workshop on Workflows in Support of Large-Scale Science (WORKS22) Archive Listing



Back to Full Workshop Archive Listing