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The ADMIRe Project and Institutional Research Data Management

The ADMIRe Project and Institutional Research Data Management. Stephen Pinfield, CIO Caroline Williams, Director of Research & Learning Resources. National and international environment. ‘Data deluge’ creating major challenges:

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The ADMIRe Project and Institutional Research Data Management

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  1. The ADMIRe Project and Institutional Research Data Management Stephen Pinfield, CIO Caroline Williams, Director of Research & Learning Resources RLUK March 2012

  2. National and international environment ‘Data deluge’ creating major challenges: Strategy: leveraging benefits for the research community and beyond Governance: decision-making and accountability Ethical: collection, management, analysis of data Risk management: including problems associated with data loss Technical: storage, retrieval of data Preservation: policy and technical issues around longevity Sharing: among collaborators, and more widely Reuse: allowing for third party mining, analysis, recombination Compliance: demonstrating compliance with funder and other policy requirements

  3. Specific drivers: external (& internal) Growth in compute power and data generation (& local HPC, data storage and e-Workbook projects) Research Council policies and requirements (& institutional policy requirement and roadmap) “Climategate” (& our own internal audit findings) Open agenda (& Open Nottingham) Role of library and IT services in managing institutional information assets (& Nottingham IS in providing join up) Governance questions (& recent governance changes with a direct line into Management Board and the Research Board)

  4. ADMIRe aims to … Develop an infrastructure to support the research data lifecycle, acknowledging & responding to differing practices across disciplines. Steered by a research data management policy endorsed at the highest level. In order to … Improve research data management capability Extend opportunities for data reuse “Open up” research data We are/will … Adopt and encourage national standards Work across University boundaries and committees Use existing expertise from within and without

  5. Project Components

  6. Staffing Structure

  7. Status High level and cross-IS support and involvement Research committee support High-level Steering Committee Cross-faculty pilots identified and commencing Recruited project team Regular internal meetings High level Research Data Management policy Data classification scheme Progress with data security

  8. Challenges Who owns managing research data? (PIs, Research Office, IT, Library) Resource requirements for set-up and maintenance of RDM infrastructure Staff knowledge, skills and cultures Speaking the same language (disciplines, across and within support services) Complexity (across disciplines) and scale (across research groups and the institution) Engagement (from researchers, support services, and governance groups)

  9. Questions, reflections and comments?

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