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Birgit Plietzsch “RDM within research computing support” SALCTG June 2013

  1. Dr Birgit Plietzsch, Research Computing Team Leader RDM within Research Computing support SALCTG, 18 June 2013
  2. RDM: The destination “The next generation of scientific discovery will be data-driven discovery. ... We need to make sure we capture value from this mass of data – both for economic growth and for social advances, such as better health. ... This requires a transformation in data management.” (Speech by the Chancellor of the Exchequer, Rt Hon George Osborne MP, to the Royal Society (9 November 2012)) “As a first step towards this intelligent openness, data that underpin a journal article should be made concurrently available in an accessible database. We are now on the brink of an achievable aim: for all science literature to be online, for all of the data to be online and for the two to be interoperable.” (The Royal Society. Science as an Open Enterprise: The Royal Society Science Policy Centre Report 02/12 (June 2012), p. 7)
  3. • National / international effort: – Economic benefits – Subject-specific, not institutional • RDM affects the entire University: – Training and advice: • Creation • Access & Sharing • Metadata • Appraisal and selection – Storage and technical maintenance – Cataloguing – Physical space: • ICT infrastructure • Paper records – Strategies, policies and procedures: • University-level • HR • Service-level – Cost recovery • Finance Advice and Support team • Requirement for processes: – RDM planning: • Project • Service providers • Long-term access: – Digital preservation RDM: The journey Research Computing Service interfaces with RDM • Training & advice: data creation, long- term storage, technical standards • Storage and technical maintenance • Service-level strategy & procedures • Cost recovery • RDM planning (at project and service level) • Technical solutions for RDM and digital preservation
  4. Research Computing Service 2003 Arts Computing Advisor 2008 Developer for Arts and Humanities projects 2011 Research Computing Service 2013 University approval for 2 new posts: - Research Computing Advisor - Applications Developer (Research Computing) Vision To provide innovative and advanced digital technologies and research computing services of nationally and internationally recognised quality and standards, which will facilitate research excellence at the University of St Andrews. (Research Computing Strategy, )
  5. Research projects (pre-) application stage • Development of ideas Technical requirements gathering (software, hardware, technical development and data requirements) • Planning the Research Computing Service • Cost recovery Project stage • Confirmation of requirements • Technical development work • Storage and backup • Enabling access & sharing • Training Post- project stage • Hosting of research outcomes  enabling access & sharing  enabling use & re-use • Technical maintenance • [long-term preservation] University / service view
  6. Research projects Funder perspective •“This is an exceptionally well written proposal, setting out its general goals with clarity. The applicant gives confidence at every level, presenting few issues for thought or clarification. The digital outcomes are well defined, and supported by relevant resources and management. This is likely to produce a very successful resource, with usefulness to scholars and the general public alike.” Quality of applications •“The IT people will be very important in this project, and I don't know them, but certainly the on-line databases provided by St Andrews which I have used are reliable both technically and intellectually. It seems safe to assume, therefore, that this side of things will also be successful.” Technical support / skill available to the project team •“It is good to see the technical work being carried out in the context of an institutional commitment to the digital humanities, as evidenced by the University's Arts Research and Teaching Server and the support of the university's Research Computing Team.” Institutional commitment / sustainability of project outcomes
  7. Research Computing Service Generic needs School 1 • Project 1a • Project 1b School 2 • Project 2a • Project 2b School 3 • Project 3a • Project 3b Shared solution Repository-type solutions Image database ( Digital Archive Digital Collections Repository ( reduction of resource required for development and technical maintenance speed of service subject & project-specific description needs
  8. Impact of RDM on the service • Formalisation of procedures – RDM planning (DMPonline?) – Service review (Data Asset Framework, CARDIO) • Increase in scale and volume of activities • Increased co-operation with other parts of the University • Technically accommodate better use and re-use of data • Long-term storage requirement – Digital preservation starts at the point of data creation! • Cost recovery
  9. Data Asset Framework (DAF) • Framework for auditing of departmental data collections, awareness, policies and practice for data curation and preservation – Online tool: • Get an idea of current RDM practices within academic Schools • Interviews using open questions: – Managing Data – Access and Sharing – Preservation and Archiving – Existing RDM support provision – RDM policy
  10. DAF Action Points (Science Schools) • Provide training in RDM • Produce a comprehensive list of services offered centrally • Improve the responsiveness and flexibility of central services to better meet the needs of researchers • Undertake extensive outreach and advocacy work to build awareness of and trust in central services
  11. DAF Action Points (Arts Schools) • Confirmation of existing central research computing support service provision: – Applications for funding / RDM planning – Technical development work – Training • Long-term storage / digital preservation • Requests for support of unfunded research
  12. Collaborative Assessment of Research Data Infrastructure and Objectives (CARDIO) • Benchmarking tool for data management strategy development, typically applied at the department or research group level – Online tool: • Involvement: – Data creators (DAF) – Information managers – Service providers • Monitor service provision – Alignment with institutional goals and academic requirements
  13. Use and re-use of data • Technology can accommodate some of this • Development of flexible solutions – APIs • Programming code is data! – Open Source / Open Standard solutions • Economics • Active developer community • Long-term commitment • Visualisation / Analysis tools
  14. Long-term access • Need for digital preservation: – What? – How? – How long for? • Technical and procedural components – Digital archiving project
  15. Open Archival Information System (OAIS) ISO 14721:2003 Functional Overview
  16. OAIS procedural overview
  17. Cost of RDM • For example: – Hardware – Software – Storage & backup • Rule of thumb: 1TB = £30k over 25 years – Staff: • Hardware implementation and maintenance • Technical development • preparation of the data for access and curation (incl. the addition of metadata) • Data collection • Data analysis • Sharing
  18. Cost of RDM: Funder perspective • RCUK Common Principles on Data Policy ( – Principle 7: “It is appropriate to use public funds to support the management and sharing of publicly-funded research data. To maximise the research benefit which can be gained from limited budgets, the mechanisms for these activities should be both efficient and cost-effective in the use of public funds.” • Efficient use of such money • Funders are looking for research benefits where money is spent. – Principle 2: “Institutional and project specific data management policies and plans should be in accordance with relevant standards and community best practice. Data with acknowledged long-term value should be preserved and remain accessible and usable for future research.” • Not all data should remain accessible or be preserved. • Retention of data is the decision of the researcher. If data is kept, it should be kept in accordance with funder policies.
  19. Cost of RDM: Funder perspective • DMP: principles under which the data is going to be made available • Institutional plan, policy or operational document: institutional infrastructure that is provided for making data available • Justification of Resources of applications for funding: – What exactly it is that they expect funders to pay? • the cost of collecting data • the cost of curating data • the cost of analysing data • the cost of preservation and sharing • Further detail:
  20. Further resources • DCC web site: • JISC MRD – Some projects to look at via: • Books – Graham Pryor (ed.) Managing Research Data (2012) – Adrian Brown. Practical Digital Preservation (2013)
  21. Summary • RDM requires co-operation across institutions • Research Computing: – Contribute towards RDM planning – Provide and maintain technical solutions – Contribute towards costings / institutional cost recovery – Contribute towards RDM training • RDM is bigger than that!
  22. Any questions ? Dr Birgit Plietzsch, Research Computing Team Leader 01334 462315 @birgitplietzsch blog: