DPHEP "H2020 brain-storming"

Europe/Zurich
31/3-004 - IT Amphitheatre (CERN)

31/3-004 - IT Amphitheatre

CERN

105
Show room on map
EINFRA-1
EINFRA-9
INFRADEV-4
    • 1
      Goals
      The goal of this meeting is not to define precisely the work packages and details of possible H2020 projects but to agree on recommendations to take forward to the EU-T0 and other relevant meetings focussing on H2020 project proposal preparation.

      The window for preparing the projects in earnest is mid-May to mid-July 2014, with a deadline for submission of 2 September 2014.

    • 2
      EINFRA-1: possible projects
      • a) Clean slate approaches to data management targeting 2020+ 'data factory' requirements of research communities and large scale facilities
        JDS: this is not strictly speaking a "data preservation" issue but IMHO is a clear opportunity for "EU-T0" / EIROforum / related institutes and projects to bid for.

        Q: who is providing the support and solutions for these "next generation" data factories: SKA, HL-LHC, FCC etc.

      • b) Cost-effective and interoperable solutions for data management and long term preservation.
        Including certification, demonstration of high level of service, sustainability.

        This should / could build on what has been co-funded by FP7 (and prior) EU projects, so need not be in conflict with EUDAT / EGI / EU-T0 (and could in fact be synergistic).

        We seem to be unique in terms of:

        • Our proven scale;
        • Our proven level of service:
        • Our understanding of the costs and plans / predictions for 1-2 decades.
    • 3
      VRE: possible projects
      Assuming something like ISO 16363 / DSA is covered in the infrastructure area, can we address our scientific, cultural and educational goals in the VRE calls? (EINFRA-9 and complementarity with INFRADEV-4, covering CTA, SKA, XFEL etc.)

      Specifically:

      • Open Data for Educational Outreach
      • Reproducibility of results
      • Maintaining the full scientific potential of the data
    • 4
      Wrap-up and Next Steps