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The Back-End of a Two-Layer Model for a Federated National Datastore for Academic Research VOs that Integrates EGEE Data Management

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Abstract

This paper proposes an architecture for the back-end of a federated national datastore for use by academic research communities, developed by the e-INIS (Irish National e-InfraStructure) project, and describes in detail one member of the federation, the regional datastore at Trinity College Dublin. It builds upon existing infrastructure and services, including Grid-Ireland, the National Grid Initiative and EGEE, Europe’s leading Grid infrastructure. It assumes users are in distinct research communities and that their data access patterns can be described via two properties, denoted as mutability and frequency-of-access. The architecture is for a back-end—individual academic communities are best qualified to define their own front-end services and user interfaces. The proposal is designed to facilitate front-end development by placing minimal restrictions on how the front-end is implemented and on the internal community security policies. The proposal also seeks to ensure that the communities are insulated from the back-end and from each other in order to ensure quality of service and to decouple their front-end implementation from site-specific back-end implementations.

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Authors and Affiliations

  1. School of Computer Science and Statistics, Trinity College Dublin, Dublin 2, Ireland

    Brian Coghlan, John Walsh, Stephen Childs, Geoff Quigley, David O’Callaghan, Gabriele Pierantoni, John Ryan & Neil Simon

  2. Dublin Institute for Advanced Studies, Dublin 2, Ireland

    Keith Rochford

Authors
  1. Brian Coghlan
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  2. John Walsh
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  3. Stephen Childs
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  4. Geoff Quigley
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  5. David O’Callaghan
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  6. Gabriele Pierantoni
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  7. John Ryan
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  8. Neil Simon
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  9. Keith Rochford
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Correspondence to Geoff Quigley.

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Coghlan, B., Walsh, J., Childs, S. et al. The Back-End of a Two-Layer Model for a Federated National Datastore for Academic Research VOs that Integrates EGEE Data Management. J Grid Computing 8, 341–364 (2010). https://doi.org/10.1007/s10723-010-9149-9

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