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Integrated e-Infrastructure for Scientific Facilities

Integrated e-Infrastructure for Scientific Facilities. Kerstin Kleese van Dam STFC- e-Science Centre Daresbury Laboratory K.kleese@dl.ac.uk. Science and Technology Council Facilities.

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Integrated e-Infrastructure for Scientific Facilities

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  1. Integrated e-Infrastructure for Scientific Facilities Kerstin Kleese van Dam STFC- e-Science Centre Daresbury Laboratory K.kleese@dl.ac.uk

  2. Science and Technology Council Facilities • We employ more than 2200 staff who are deployed at 7 locations, these are:Swindon where the headquarters is based: the Rutherford AppletonLaboratory, the Daresbury Laboratory, the Chilbolton Observatory, the UK Astronomy Technology Centre in Edinburgh, the Isaac Newton Group of Telescopes on La Palma; and the Joint Astronomy • Centre in Hawaii.

  3. Research and Science Support at STFC • Deliver world class science • Engender world class science • Communicate world class science • Annually over 15000 visiting Scientists from around the world from both Academia and Industry.

  4. HPC Experiment Storage Analysis HPC Scientist Experiment Computing Storage Analysis HPC Why we need an Integrated e-Infrastructure

  5. What we aim to achieve with the e-Infrastructure • Enabling users to get rapid access to their current and past data,related experiments, publications etc., leading to improved analysis through more complete information. • Creating a powerful, long lasting scientific knowledge resource.

  6. Data Analysis Data Acquisition System Experiment Publication Information Proposal System Metadata Catalogue Secure Storage Integrated e-Infrastructure All Data and Metadata Capture is automated. Proposal E-Pubs

  7. CSL - Canada SNS - ORNL CLF ISIS – TS1 + 2 DLS SRS + ERLP e-Infrastructure – Access to Multiple Facilities(2) Data Portal

  8. HPC Experiment Storage Analysis HPC Experiment Computing Storage Analysis HPC How we achieve the integration Metadata Scientist

  9. CDR Facility User Views on CDR (representing this schema) SSO Views on CDR (representing this schema) Context Account People People_ address People_ Establish- ment Identity Admin ULO Admin Address Establish -ment Attribute Establish- ment _Address Facility ULOs SSO Portal Facilities E-Science CRIS – Identity Management System

  10. Keywords providing a index on what the study is about. Provenance about what the study is, who did it and when. Conditions of use providing information on who and how the data can be accessed. Detailed description of the organisation of the data into datasets and files. Locations providing a navigational to where the data on the study can be found. References into the literature and community providing context about the study. Core Scientific Metadata Model Metadata Object Topic Study Description Access Conditions Data Description Data Location Related Material

  11. Core Scientific Metadata Model (2) • Detailed Information about Instrument and Experiment such as: • Sample Information and Parameter • Experimental Station and Set Up • Environmental Parameters • Key Parameters from the Data • Keywords and Classifications

  12. Core Scientific Metadata Model (3) • Detailed Information about the Data Analysis and underpinning Computational Simulations: • Simulation/Analysis Code and version • Simulation Set-up and Parameters • Information about the Compute Resource • Key Parameter from the Simulation Results • Keywords and Classifications

  13. What we have achieved • Agreed common metadata and data formats and single sign on allow scientist to have rapid access at any stage of their work to: • Present and past projects at STFC. • Publications • Raw data from DLS, ISIS and CLF. • Advanced Analysis Software and High Performance and High Throughput Computing • Advanced Visualisation • enabling improved analysis

  14. What we have achieved (2) • A 20 year back catalogue of ISIS raw data is available. • A similar catalogue for SRS data is currently being created. • All future data collected at STFC Facilities and DLS will be curated and made available for reuse now and in the future. • Creating a powerful, long lasting scientific knowledge resource.

  15. Future Challenges • Data Policy and Ownership. • Data and Metadata Curation for long-term reuse. • Enabling scientist to use information from unfamiliar methods. • Integration with other Facilities around the world.

  16. Summary • First e-Infrastructures are here. • Metadata is key to the integration of Research Processes. • Scientist benefit greatly from e-Infrastructures. • There are more Challenges ahead.

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