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Research Data Management Storage Requirements: University of Leeds


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Research Data Management Storage Requirements Workshop, Mon 25 February, organised by Jisc, Janet and DCC. Presentation covers a research data survey, the RoaDMaP project, research data characteristics and potential storage requirements at the University of Leeds.

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Research Data Management Storage Requirements: University of Leeds

  1. 1. RDM Data Storage WorkshopFebruary 25th 2013Brian CliffordUniversity of Leeds
  2. 2. The University of Leeds: Institutional Context• 1,500 researchers (plus postgrads)• £130m research income• 80% RCUK Funded• 9 Faculties – Devolved budgets – Faculty based support for researchers• Development of a Central RDM including The Library, Research and Innovation Office, IT Service, Staff Development supporting staff based in Faculties• Investigations being undertaken by the JISC funded RoaDMaP Project
  3. 3. How much research data do you typically generate in a year?
  4. 4. What % research data would you need to keep for others to validate yourresearch findings?
  5. 5. RoaDMaP considering aspects of Long term storage• Tested use of F5 systems for virtual storage• Archiving as a service – e.g. Arkivum – Currently working on proof of concept depositing / retrieving large files• Plan to investigate feasibility of integration with ePrints for retrieval of archived datasets.• Pros and cons of outsourcing vs consortial options vs institutional options• Does outsourcing help direct cost recovery from grants?• Consortial options: – White Rose (DCC Institutional Engagement Project) – N8 (parallels with HPC model)?
  6. 6. Funding options• Considering three different models for the funding of the institutional research data management service – Top slice through RAM from Faculty income to pay for central service – Strategy Development Funding (one off!) – Recharge model• Investigating all three to ensure that the model chosen does not lead to negative behaviours• What can we afford, what do we need to store?
  7. 7. RDM Storage RequirementsGraham BlythJISC RoaDMaP ProjectEngineering IT
  8. 8. Current estimate of required storage volume?• MAPS 1 PByte• Environment 1 PByte• M+H 0.3 PByte• FBS 0.25 PByte• Engineering 0.1 PByte*
  9. 9. Research Scenarios • Large volume – expensive - changing • Large volume – expensive – static • Large volume – cheap – static or changing • Small volume – expensive • Shared access • Rate of creation • Performance in use
  10. 10. Research Scenarios – Flame frontsRaw data - High speed camera – large data, expensive experimentProcessed camera data – large data, moderately expensive processParticle detection – moderate data, moderately expensive computationSoftware development – small data, very expensive
  11. 11. Research Scenarios Characteristic Implication for StorageRaw Camera data Cost to reproduce very high Permanent long term storage Shared access Access control Very large volume of data Dedicated network storage High speed access needed Local copy may be required
  12. 12. Types of Data Static Changing Live/Archive Cheap Published/Repository Expensive
  13. 13. Storage – focus on value axisScratch –– cheap static or changing dataBacked-up –– traditional fully managed storageRepository –– discipline repositories and growing institutional or regionalrepositoriesArchive –– ?
  14. 14. With an Archive for this ScenarioStore raw camera data in archiveMay keep local copy on scratch disk for performanceSimplified backupCapture metadata at time of data creationCommon scenario – estimate 80% of expensive Engineering data
  15. 15. Components of research data management support services Business Plan andRDM Policy and Roadmap Sustainability Data Management Planning Data Managing Active Data Repositories/Catalogues Processes for selection Deposit and Handover and retention Guidance, Training and Support