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DTSTART;TZID=Europe/Stockholm:20260629T160000
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UID:submissions.pasc-conference.org_PASC26_sess126@linklings.com
SUMMARY:MS2G - Data Management in Scientific Workflows
DESCRIPTION:Access the recording\n\nOrganizer(s): Florine Willemijn de Geu
 s (CERN, University of Twente), Vincenzo Eduardo Padulano (CERN), and Ana-
 Lucia Varbanescu (University of Twente)\n\nData-driven research methods ha
 ve become essential for many scientific domains, such as earth sciences, h
 igh-energy physics, material science, or biomedical engineering. Within th
 ese domains, data is collected with different tools, stored in different f
 ormats and systems, organized and accessed in typical workflows, and overl
 y-tuned towards the domain requirements. Additionally, the data-management
  practices by which data is collected, prepared, processed, and shared var
 y a lot, ranging from highly centralized to small-scale and perhaps siloed
  approaches. We propose this minisymposium as a forum for experts to share
  and discuss practices, requirements and challenges for data management. O
 ur aim is to highlight best practices and challenges across the breadth of
  scientific computing and establish a common understanding of scientific d
 ata management, to enable the co-design of HPC methods and tools for a div
 erse portfolio of data-driven, cross-domain scientific workflows and resea
 rch infrastructure. This minisymposium will consist of three 25-minute pre
 sentations, followed by a Q&A session organized as a panel with the presen
 ters. For all our invited speakers, we gave the same assignment: introduce
  your research and ideas through the lens of demand and offer for next gen
 eration data management for scientific computing. This will be the focus o
 f the panel, as well.\n\nRDM vs Science-First Thinking About Data Manageme
 nt\n\nResearch Data Management (RDM) is crucial for ensuring research inte
 grity, reproducibility, and reuse, while maximizing the impact and visibil
 ity of scientific findings. As such, RDM and the FAIR principles are pilla
 rs of open science. In the last decade, RDM has been widely implemented, s
 upported b...\n\n\nRob van Nieuwpoort (Leiden University)\n---------------
 ------\nData Storage and Management for High-Energy Physics\n\nBetween the
  four main experiments at CERN’s Large Hadron Collider, an estimated 2 EB 
 of high-energy-physics (HEP) data has been recorded and stored since 2009.
 \nEach experiment is governed by a large collaboration, consisting of over
  one hundred institutes from all over the world. The scale of ...\n\n\nFlo
 rine Willemijn de Geus (CERN, University of Twente)\n---------------------
 \nKVCache Data Management in Distributed GenAI Workloads: Characteristics,
  Requirements, and Challenges\n\nGenerative AI (GenAI) workloads — code co
 mpletion, intelligent agents, semantic RAG, and recommender systems — have
  become widely adopted across many domain-specialized settings. These syst
 ems run on large-scale, high-performance infrastructure of thousands of GP
 Us, storage, and networki...\n\n\nAnimesh Trivedi (IBM Research)\n--------
 -------------\nPanel Session\n\nThis session will be dedicated to a panel 
 discussion and Q&A of the presenters of this minisymposium. Our aim is to 
 identify and discuss common practices and challenges, and share ideas on h
 ow to overcome these challenges and ultimately contribute to HPC systems c
 o-design.\n\n\nVincenzo Eduardo Padulano (CERN)\n\nDomain: Climate, Weathe
 r, and Earth Sciences, Life Sciences, Physics, Computational Methods and A
 pplied Mathematics\n\nSession Chair: Vincenzo Eduardo Padulano (CERN)
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