The ADMIRe Project and Institutional Research Data Management

Stephen Pinfield, CIO

Caroline Williams, Director of Research & Learning Resources

RLUK March 2012

‘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

2

National and international environment

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)

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 …

1.Improve research data management capability

2.Extend opportunities for data reuse

3.“Open up” research data

We are/will …

1.Adopt and encourage national standards

2.Work across University boundaries and committees

3.Use existing expertise from within and without

Project Components

Staffing Structure

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

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)

Questions, reflections and comments?