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EPOS e-Infrastructure

EPOS e-Infrastructure. Keith G Jeffery Natural Environment Research Council keith.jeffery@stfc.ac.uk (with Jean-Pierre Vilotte and Alberto Michelini). Structure of Presentation. Who? EPOS Rationale and approach e-Infrastructure Basics Related Projects (Torild van Eck) Proposed Approach

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EPOS e-Infrastructure

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  1. EPOS e-Infrastructure Keith G Jeffery Natural Environment Research Council keith.jeffery@stfc.ac.uk (with Jean-Pierre Vilotte and Alberto Michelini)

  2. Structure of Presentation • Who? • EPOS Rationale and approach • e-Infrastructure Basics • Related Projects (Torild van Eck) • Proposed Approach • Conclusion

  3. Rutherford Appleton Laboratory STFC Rutherford Appleton Laboratory

  4. Structure of Presentation • Who? • EPOS Rationale and approach • e-Infrastructure Basics • Related Projects (Torild van Eck) • Proposed Approach • Conclusion

  5. EPOS Rationale

  6. EPOS Concept Massimo Cocco

  7. Structure of Presentation • Who? • EPOS Rationale and approach • e-Infrastructure Basics • Related Projects (Torild van Eck) • Proposed Approach • Conclusion

  8. e-Infrastructure Basics • GRIDs • Clouds • Web 2.0 • SOA (Service-Oriented Architecture) • Research process • Fourth paradigm (Data Intensive Scientific Discovery) • Virtualisation • Autonomicity • Security, Privacy, Trust • Performance • Development • Maintenance

  9. Internet 1.5 billion fixed connections Estimated 4 billion mobile connections Digital Storage Estimated 280 billion Gigabytes (280 exabytes – 280*10**18) Expect all to grow ~ 1 order of magnitude in 4 years and accelerating) Users : Asia 550 million 14% penetration Europe 350 million 50% penetration USA 250 million 70% penetration Scalability Trust & security & privacy Manageability Accessability Useability Representativity CONTEXT Last 20 years CPU 10**16 Storage 10**18 Networks 10**4

  10. Knowledge Layer Information Layer Data toKnowledge Control Computation / Data Layer The GRIDs Architecture: Layering The GRIDs Architecture

  11. Cloud Computing: The Intention • Low cost of entry for customers • Device and location independence • Capacity at reasonable cost (performance, space) • Cloud Operator manages resource sharing balancing different peak loads • Scalable as demand rises from user • Security due to data centralisation and software centralisation • Sustainable and environmentally friendly – concentrated power •  it is a service and the user does not know or care from where, by whom, and how it is provided •  as long as the SLA (service level agreement) is satisfied

  12. Web 2.0 • Features: • creativity, communications, secure information sharing, collaboration and functionality • Examples: • Social networking, video-sharing, wikis, blogs, folksonomies • Crowdsourcing to gather information / knowledge wisdom? If you don’t know what Web2.0 is your kids do!

  13. server server server server Bringing it Together: e-,i-,k-infrastructure k- Deduction & induction – human or machine i- Information Systems e- server Physical detectors

  14. Middleware – and as SOKUs (Service-Oriented Knowledge Utilities) k- K- upper middleware (resolves semantic heterogeneity) K- lower middleware (presents declared semantics) i- Upper middleware (hides syntactic heterogeneity) Lower middleware (hides physical heterogeneity) e-

  15. Research Process: 4th Paradigm Observational Science Experimental Science Modelling Science Hypothesis Characterisation Simulation/modelling Observations Contextual metadata Pre-processing Digital preservation Availability Analysis Visualisation Hypothesis Experimentation Observations Contextual metadata Pre-processing Digital preservation Availability Analysis Visualisation • Observations • Contextual metadata • Pre-processing • Digital preservation • Availability • Analysis • Visualisation (Concept from Jim Gray 1944-2007) DATA-INTENSIVE SCIENCE

  16. Structure of Presentation • Who? • EPOS Rationale and approach • e-Infrastructure Basics • Related Projects (Torild van Eck) • Proposed Approach • Conclusion

  17. Related Projects EPOS e-infrastructure has to fit in with • ESFRI Roadmap projects in Environmental Cluster (ENVRI) • ESFRI roadmap projects in other clusters • Physical sciences (STM) • Astronomy & Astrophysics • Economic/social science • Arts and humanities • PRACE (supercomputing) • EGI/NGIs (Data and Computing Grid) • European INFRA projects (VERCE, EUDAT…) • National e-infrastructures for e-Research • Especially geoscience • Other international projects (North America, Japan, Pacific Rim, South America…)

  18. EPOS IT relevant EC-project projects + proposal (summary) GEM Hazard EC projects starting 2010 SHARE Hazard ETHZ (D. Giardini) NERA Seismology & Seismic Engineering ETHZ + ORFEUS/KNMI (D. Giardini; T. van Eck) EPOS PP Solid Earth ESFRI project INGV (Massimo Cocco) QUEST (Training network) Computational Seismology LMU (H. Igel) EPOS (ESFRI roadmap) Under negotiation VERCE Earthquake & Seismology CNRS-IPGP (J-P Vilotte) UEDIN ORFEUS/KNMI EMSC INGV LMU Univ Liverpool BADW-LRZ CINECA Fraunhofer/SCAI INFRA-2011-1.2.1 EUDAT Data Infrastructure CSC Finland (Kimmo Koski) EPOS (GFZ, INGV) LifeWatch … CINECA UEDIN … INFRA-2011-1.2.2 ENVRI Environment Research Infrastructure LifeWatch (Wouter Los) EPOS (ORFEUS/KNMI) LifeWatch EPOS EMSO EISCAT ICOS STFC UEDIN … INFRA-2011-2.3.3 Under negotiation Under negotiation Project proposals 2010 INFRASTR. 2011-1 Call 8/9

  19. Structure of Presentation • Who? • EPOS Rationale and approach • e-Infrastructure Basics • Related Projects (Torild van Eck) • Proposed Approach • Conclusion

  20. e-Infrastructure Requirement • Data collection, calibration, validation • Data cataloguing and indexing • Data preservation and curation • Information processing – retrieval, analysis, visualisation • Hypothesis processing – simulation, modelling, analysis, visualisation • Hypothesis generation – data mining • Knowledge processing – integration of ICT with human processing – theory processing, user interface, scholarly communication (open access) • External interoperation – physical and medical sciences, economic and social sciences, arts and humanities • Dissemination – outreach (website plus) • Education and training • Management and Coordination

  21. Key e-Infrastructure Principles • Mobile code: ability to move code to data because data large and costly to transport • Virtualisation: user neither knows nor cares where computing done or where data located as long as QoS/SLA met • Autonomicity: (self-*) because human management of ICT too expensive / slow

  22. Key e-Infrastructure Challenges • Interoperation • Access to heterogeneous distributed data sources • Schema integration – syntactic and semantic • Security/privacy/trust • Identification – authentication – authorisation – accounting • Performance • Towards exascale processing (simulation/modelling) • Towards exabyte data streams (1.0*10**18)

  23. Steps to achieve EPOS e-Infrastructure1 • Define / Agree requirements of end-user (document dynamically) • Including expected future requirements • Survey available data/information sources (document dynamically) • Detector systems • Repositories / databases / file systems • Data, documents, metadata, contextual data • Conditions of use – QoS, SLA (link to governance) • Define schema mappings, convertors for interoperation (document dynamically) • Canonical interoperation standard? • Note CERIF (Common European Research Information Format)

  24. Steps to achieve EPOS e-Infrastructure2 • Survey available computing and computation resources (document dynamically) • Detector systems • Data servers • HPC • Conditions of use – QoS, SLA (link to governance) • Define access and utilisation of ICT (document dynamically) • User identification, authentication, authorisation, accounting (security, privacy) • Available services • Conditions of use – QoS, SLA (link to governance) • Design first-cut ICT architecture (document dynamically) • GEANT network • GRIDs (EGI) middleware • Web services software • Web portal(s) user interface

  25. Structure of Presentation • Who? • EPOS Rationale and approach • e-Infrastructure Basics • Related Projects (Torild van Eck) • Proposed Approach • Conclusion

  26. Conclusion(take-home messages) • EPOS is a HUGE CHALLENGE • EPOS requires LEADING EDGE ICT to support LEADING EDGE GEOSCIENCE • EPOS e-Infrastructure is the ‘GLUE’ • EPOS is going to be FUN! • EPOS is open to collaboration ********* Prof Keith G Jeffery CEng, CITP, FGS, FBCS, HFICS keith.jeffery@stfc.ac.uk

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