Expertise: Provenance, workflow managers
Tools: Microbiology, Python
Research Engineer (Workflow Engineer) at the Barcelona Supercomputing Center (BSC) in Barcelona, Spain. Working on developing provenance features for BSC workflows.
Bachelor's degree in Physics Engineering from UPC; currently pursuing a Master's in Data Science at UPC.
Teams: Cluster Emergent del Cervell Humà, Workflows and Distributed Computing, WP6 - Tsunamis, WP7 - Earthquakes, WP8 - Anthropogenic geophysical extremes, WP5 - Volcanoes, Pillar I: Manufacturing, Pillar II: Climate, Pillar III: Urgent computing for natural hazards, eFlows4HPC general, COMPSs Tutorials
Organizations: Barcelona Supercomputing Center
https://orcid.org/0000-0003-0606-2512
Expertise: Workflows, Programming Models, High Performance Computing, Distributed Computing, Provenance
Tools: COMPSs
Established Researcher at Workflows and Distributed Computing Group, Computer Sciences department, Barcelona Supercomputing Center.
Abstract (Expand)
Authors: Simone Leo, Michael R. Crusoe, Laura Rodríguez-Navas, Raül Sirvent, Alexander Kanitz, Paul De Geest, Rudolf Wittner, Luca Pireddu, Daniel Garijo, José M. Fernández, Iacopo Colonnelli, Matej Gallo, Tazro Ohta, Hirotaka Suetake, Salvador Capella-Gutierrez, Renske de Wit, Bruno P. Kinoshita, Stian Soiland-Reyes
Date Published: 10th Sep 2024
Publication Type: Journal Article
DOI: 10.1371/journal.pone.0309210
Citation: PLoS ONE 19(9):e0309210
Presentation conducted during the Workflow Run RO-Crate bi-weekly meeting on how the Provenance Run Crate profile has been adopted by the COMPSs Workflow Management System.
Creators: Raül Sirvent, Panna Lukacs, Nicolò Giacomini
Submitter: Raül Sirvent
Provenance registration is becoming more and more important, as we increase the size and number of experiments performed using computers. In particular, when provenance is recorded in HPC environments, it must be efficient and scalable. In this paper, we propose a provenance registration method for scientific workflows, efficient enough to run in supercomputers (thus, it could run in other
...
Creator: Raül Sirvent
Submitter: Raül Sirvent
The Human–AI Ledger (HAIL) defines a structured, repeatable workflow for human–AI collaboration. Through standardized checkpoints and a session ledger, HAIL documents ethical, creative, and procedural context across both human and AI contributions. While AI-generated outputs are inherently non-deterministic, HAIL supports process reproducibility by providing a consistent framework for recording collaboration, facilitating auditability, transparency, and ethical accountability in co-creative AI ...
Type: Unrecognized workflow type
Creators: Evan P. Troendle, BioFAIR Fellowship Programme
Submitter: Evan P. Troendle
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