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Institutional Data Management Blueprint


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A talk by Kenji Takeda, given at the Eduserv Symposium 2011 - Virtualisation and the Cloud.

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Institutional Data Management Blueprint

  1. 1. Institutional Data Management Blueprint<br />Kenji Takeda (Engineering Sciences), Mark Brown (University Librarian), Simon Coles (Chemistry), Les Carr (ECS, EPrints), Jeremy Frey (Chemistry), Graeme Earl (Archaeology) Peter Hancock (iSolutions), Wendy White (Library)<br />
  2. 2. Introduction<br />Why data management?<br />IDMB project <br />Key findings<br />Recommendations<br />Business plan<br />Conclusions<br /><br />2<br />
  3. 3. Data Management @ Southampton<br />What do we mean?<br />Everything<br />Why do we care?<br />Foundation for all of our research<br />How should it be managed?<br />We want to find out from users<br />How can the University help?<br />What do researchers need?<br />Key outcomes<br />Impact & profile<br />3<br />copyright © 2010 Sean Dreilinger. <br />Reproduced under Creative Commons license<br />
  4. 4. IDMB Project Overview<br />Produce framework for managing research data for an HEI<br />Scope and evaluate a pilot implementation plan for an institution-wide data model<br />4<br />
  5. 5. Review of Data Management<br />
  6. 6. Where do you store your data?<br />6<br />
  7. 7. How much electronic data do you currently retain?<br />7<br />
  8. 8. How long do you keep your data for?<br />8<br />
  9. 9. How frequently do you backup your data?<br />9<br />
  10. 10. Where do you backup your data?<br />10<br />
  11. 11. Key Findings<br />Schools research practice is embedded and unified<br />Schools data management capabilities vary widely<br />Data management is carried out on an ad-hoc basis in many cases<br />Researchers demand for storage is significant<br />Researchers resort to their own best efforts in many cases, where central support does not meet their needs<br />Users want more support for backup, particularly for large quantities of data<br />11<br />
  12. 12. Key Findings<br />Researchers want to keep their data for a long time<br />There is a need from researchers to share data, both locally and globally<br />Data curation and preservation support needs to be improved<br />12<br />
  13. 13. Gap Analysis<br />Policy and governance is robust, but is not communicated to researchers in the most accessible way<br />Services and infrastructure are in place, but lack capacity and coherence<br />There is a lack of training and guidance on data management<br />Lack of coherence and sustainable business model<br />13<br />
  14. 14. Recommendations<br />
  15. 15. Recommendations<br />Short-term (1 year)<br />Develop an institutional data repository <br />Develop a scalable business model <br />One-stop shop for data management advice and guidance<br />Medium-term (1-3 years)<br />Comprehensive and affordable backup service for all <br />Open research data mandate, and supporting infrastructure<br />Research data lifecycle management <br />Embedding data management training and support<br />15<br />
  16. 16. Long-term recommendations<br />Provide coherent data management support across all disciplines <br />Embed exemplary data management practice across the institution <br />Agile business plan for continual improvement <br />16<br />
  17. 17. Pilot Projects<br />
  18. 18. Metadata Framework<br />18<br />
  19. 19. Archaeology Data Management<br />Archaeology is all about data and metadata<br />Spectrum of data is huge<br />Laser scans<br />Photography<br />Geophysics<br />CAD<br />CGI<br />Context is everything<br /><br />
  20. 20. SharePoint 2010 Data Management<br />20<br />
  21. 21. Data Browsing in Context<br />21<br />
  22. 22. Training<br />
  23. 23. Archaeology<br />eThesis process with data<br />Exemplar: Lithic tools over 600,000 years. Looking for evidence of use in social signalling and used in visual display.<br />Examined 10,000 artefacts<br />18,300 photographs (72GB)<br />Catalogued in SPSS database<br />IPR/copyright?<br />Humanities Graduate School workshop for Easter 2011<br />23<br />
  24. 24. Chemistry<br />Embedding in UG courses<br />1st year UG intro<br />M.Chem more detailed<br />Discussion group<br />Graduate School roll-out for next intake<br />With discipline librarians<br />24<br />
  25. 25. Business planning<br />
  26. 26. Business Plan<br />Strategy<br />Principles<br />Policy<br />Infrastructure and services<br />Business model<br />Partnership approach between all stakeholders<br />Senior management, Researchers, IT, Library, Research & Innovation Services, Finance, Legal<br />26<br />
  27. 27. Institutional Data Management Policy<br />Help researchers<br />Provide guidance on what is expected<br />Provide guidance on how to manage their data<br />Help the institution<br />Define what is required<br />Comply with funders<br />Provide governance and decision-making process<br />27<br />
  28. 28. Cost Modelling<br />Data management is expensive<br />Who is responsible?<br />Who pays for it?<br />How does it scale?<br />What if somebody cannot afford it?<br />Not just about hardware<br />Sustainability<br />28<br />
  29. 29. Cloud Possibilities<br />
  30. 30. Cloud Solutions<br />Data storage demand growing at frightening rate<br />Users can accommodate this locally very cheaply<br />Difficult to satisfy with current server-based storage<br />Potential to provide:<br />Zero capital cost<br />Burst capability<br />Scalability<br />30<br />
  31. 31. Cloud Benefits<br />31<br />Diagram courtesy of Dr Steven Johnston<br />
  32. 32. Cloud Issues<br />Cost models<br />Dropbox£8k per TB<br />Data transfer charges<br />Security<br />Reliability<br />Amazon!<br />Legal implications<br />Vendor lock-in<br />32<br />
  33. 33. Conclusions<br />Good data management is vital for better research<br />Two-pronged approach<br />Bottom-up to augment researcher’s world<br />Top-down to provide support and guidance<br />Providing a roadmap for the future – including Cloud<br />33<br /><ul><li>
  34. 34.</li>