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SUMMARY:Optimizing Data Delivery and Scalable HI Profile Classification fo
 r the SKA Era: Infrastructure and Science Challenges at the Spanish SRC - 
 Dr. Manu Parra-Royón (Astrophysics Institute of Andalucia - Spanish Natio
 nal Research Council)
DTSTART:20250708T101500Z
DTEND:20250708T110000Z
UID:TALK233473@talks.cam.ac.uk
CONTACT:Charles Walker
DESCRIPTION:This talk presents ongoing work at the Spanish SKA Regional Ce
 ntre (esSRC) in the context of the SRCNet 0.1. The first part focuses on t
 he development of efficient data delivery techniques from the distributed 
 Rucio-based storage system to the SRC infrastructure and\, ultimately\, to
  user workspaces. Several approaches have been evaluated to support scienc
 e-ready access\, yet current solutions often involve unnecessary data dupl
 ication in user areas\, resulting in increased usage of storage and comput
 ational resources. To address this\, we have prototyped mechanisms based o
 n file linking\, caching\, and data reuse\, enabling more efficient access
  paths for users. While these methods show promising improvements in terms
  of performance and resource usage\, challenges remain\, particularly in t
 erms of orchestration\, scalability\, and compatibility with existing work
 load managers. The second part presents advances in the automated classifi
 cation of neutral hydrogen (HI) profiles using machine learning methods\, 
 building on previous work [Parra et al.\, 2024\, arXiv:2501.11657]. We out
 line a roadmap for extending these techniques to handle the data volumes e
 xpected from the SKA Observatory. This includes developing scalable pipeli
 nes capable of ingesting and processing large spectral datasets in a repro
 ducible and efficient manner\, and adapting the classification models to c
 ope with the diversity and complexity of the SKA data products.
LOCATION:Coffee area\, Battcock Centre
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