Managing Research Data – The Organisational Challenge at Oxford

1. Managing Research Data – The Organisational Challenge at Oxford Friday 6th December, 2013 James A J Wilsonjames.wilson@it.ox.ac.uk

2. The Growing Importance of Research Data Management • Rise of data-driven research • Challenge to existing academic practices • Opportunities for new kinds of research • Increasing recognition of need to manage research data better • Opportunities for research communities • Concern for reputations • Mandates from research funders

3. Damaro Objectives • Institutional RDM Policy • Better understanding of researchers’ requirements • Improved training & support materials – embedded in existing delivery channels • Design for connected RDM infrastructure, from planning to re-use • ‘DataFinder’ software – to act as a catalogue of research data outputs • Outputs that can be taken and adapted by other institutions(project was part of the JISC MRD Programme) • Sustainability

4. What is Research Data Management? Data analysis & research outputs File organisation & local storage Documentation Data gathering Data deposit Literature / data review Repository storage Long-term curation [Funding bid] Planning Discovery Idea Access Re-use

5. Principles behind Oxford’s infrastructure • Modular • Different business models for different components • May be extended (or reduced) • Researcher-focused • Caters for different disciplines and working practices • Intra-institutional • Requires input from multiple support departments and Academic Divisions

6. Demand

7. Demand for support with RDM from researchers Importance of RDM “My supervisor doesn’t want the whole dataset to be made publicly available as it is. However, he is very keen that whenever research papers based on the data are published, relevant portions of the data that support the findings are also published.” “Having a secure and fairly straightforward means by which to share data with selected collaborators around the world would be extremely useful.” “It would be useful for graduate students to learn to pick the appropriate tool for the appropriate question and the appropriate data … to know what their options are.” But fewer than a quarter had received any information about RDM from the University

8. Training Desired Common RDM tasks ranked by mean level of desire for training :5 = most desired, 1 = least desired

9. Demand for support with RDM from above “Publicly funded research data are a public good, produced in the public interest, which should be made openly available with as few restrictions as possible in a timely and responsible manner.” RCUK Common Principles on Data Policy “data must be accessible and readily located; they must be intelligible to those who wish to scrutinise them; data must be assessable so that judgments can be made about their reliability and the competence of those who created them; and they must be usable by others. For data to meet these requirements it must be supported by explanatory metadata (data about data).” Royal Society – Data as an Open Enterprise

10. Challenges

11. Diverse practices • Principle of subsidiarity • 45% of Departmental IT Managers reported that ‘every researcher / research group is completely free to choose how they manage their research data’ • 70% offer some departmental infrastructure to encourage a degree of standard practice (e.g. shared drives, data deposit guidelines) • 15% of departments have a departmental policy mandating particular tools and processes that researchers should use for managing their data • University RDM policy ratified in 2012, setting out responsibilities of researchers and institution

12. Disciplinary requirements differ • Significant differences in how researchers work • Wide range of experience and confidence amongst researchers • Some disciplines already have good RDM infrastructure in place, some keen for central support • “The University should have a dedicated central repository” • “[The University should] develop a data management service or be in a position to know what to recommend to our researchers” • “The desire to centralize … may work at the lower end of the data requirements, but at the higher end is rather naïve”

13. Researchers unclear where to go for support

14. Lack of staff confidence with RDM issues Completely Confident Not Confident

15. Solutions

16. Who should support research data management? IT Services Data analysis & research outputs File organisation & local storage Documentation Data gathering Data deposit Academic Divisions & Departments Literature / data review COORDINATION Repository storage Oxford eResearch Centre (OeRC) Long-term curation [Funding bid] Library Services Planning Discovery Research Services Idea Access andre-use

17. Role of Libraries • Metadata • Access • Workflows • Collection management • Collection curation and preservation • Service provision • Systems • But also contributions to training and good practice in earlier parts of research life-cycle

18. Ongoing work • Research services • OxfordDMPOnline & 20 questions for RDM • Involvement of research facilitators • IT Services • Implementing services for ‘live’ data (HFS, Servers and VMs, Supercomputing, ORDS) • Research Support Group • Libraries • DataBank • DataFinder • Involvement of Subject Librarians • University coordination • Research Data Management and Open Data Working Group

19. Coordination • Single point of contact • Central RDM website • Associated challenges • Information / data / metadata flows • RT systems • Resourcing • More organisational than technical

20. Questions?