Comprehensible control for researchers and developers facing data challenges

Malcolm Atkinson, Rosa Filgueira, Iraklis Klampanos, Antonis Koukourikos, Amrey Krause, Federica Magnoni, Christian Page, Andreas Rietbrock, Alessandro Spinuso

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The DARE platform enables researchers and their developers to exploit more capabilities to handle complexity and scale in data, computation and collaboration. Today's challenges pose increasing and urgent demands for this combination of capabilities. To meet technical, economic and governance constraints, application communities must use use shared digital infrastructure principally via virtualisation and mapping. This requires precise abstractions that retain their meaning while their implementations and infrastructures change. Giving specialists direct control over these capabilities with detail relevant to each discipline is necessary for adoption. Research agility, improved power and retained return on intellectual investment incentivise that adoption. We report on an architecture for establishing and sustaining the necessary optimised mappings and early evaluations of its feasibility with two application communities.

Original languageEnglish
Title of host publicationProceedings - IEEE 15th International Conference on eScience, eScience 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages311-320
Number of pages10
ISBN (Electronic)9781728124513
DOIs
Publication statusPublished - Sept 2019
Event15th IEEE International Conference on eScience, eScience 2019 - San Diego, United States
Duration: 24 Sept 201927 Sept 2019

Publication series

NameProceedings - IEEE 15th International Conference on eScience, eScience 2019

Conference

Conference15th IEEE International Conference on eScience, eScience 2019
Country/TerritoryUnited States
CitySan Diego
Period24/09/1927/09/19

Keywords

  • Conceptualisation
  • Data-driven science
  • HPC on cloud
  • Multi-everything CSCW
  • Provenance
  • Scientific workflows

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