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DTSTAMP:20250626T234540Z
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DTSTART;TZID=America/New_York:20241118T091400
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UID:submissions.supercomputing.org_SC24_sess756_ws_worksp110@linklings.com
SUMMARY:A software Ecosystem for Multi-Level Provenance Management in Larg
 e-Scale Scientific Workflows for AI Applications
DESCRIPTION:Gabriele Padovani (University of Trento, Italy); Valentine Ana
 ntharaj (Oak Ridge National Laboratory (ORNL)); Ludovica Sacco (University
  of Trento, Italy); Takuya Kurihana (Oak Ridge National Laboratory (ORNL))
 ; Matteo Bunino, Kalliopi Tsolaki, and Maria Girone (European Organization
  for Nuclear Research (CERN)); Fabrizio Antonio (Euro-Mediterranean Center
  on Climate Change Foundation); and Carolina Sopranzetti, Massimiliano Fro
 nza, and Sandro Fiore (University of Trento, Italy)\n\nScientific workflow
 s and provenance are two faces of the same medal. While the former address
 es the coordinated execution of multiple tasks over a set of computational
  resources, the latter relates to the historical record of data from its o
 riginal sources. This paper highlights the importance of tracking multi-le
 vel provenance metadata in complex, AI-based scientific workflows as a way
  to (i) foster and (ii) expand documentation of experiments, (iii) enable 
 reproducibility, (iv) address interpretability of the results, (v) facilit
 ate performance bottlenecks diagnosis, and (vi) advance provenance explora
 tion and analysis opportunities.\n\nTag: Applications and Application Fram
 eworks, Distributed Computing, Middleware and System Software\n\nRegistrat
 ion Category: Workshop Reg Pass\n\nSession Chairs: Silvina Caino-Lores (Fr
 ench Institute for Research in Computer Science and Automation (INRIA)) an
 d Anirban Mandal\n\n
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