Andrew Cox Research data management


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Andrew Cox Research data management

  1. 1. Online Information 2013, 20th November, Victoria Park Plaza, London The academic library’s role in research data management Andrew Cox, Information School, University of Sheffield Nov-13
  3. 3. What is research data? Variety • • • • • • • • • Weather measurements Photographs Results from experiments Government records GIS data Simulation data Log data Field notes Software Nov-13 • Images (e.g. brain scans) • Quantitative data (e.g. household survey data) • Historical documents • Moving images • Physical objects: such as bones or blood samples • Digitised photos / born digital photos • Social media data: tweets • Metadata Learning material produced by RDMRose
  4. 4. Duffy (2013) on scale of the data issue at University of Birmingham • • • • • • 3000 items in institutional repository 50,000 items in special collections 75,000 publications for REF 2,700,000 items in library 700,000,000 folders in top 100 accounts Volume Perhaps 1,000,000,000 folders for the whole university Nov-13 Learning material produced by RDMRose
  5. 5. Complexity of information practices • Information flow maps for life science research (RIN, 2009) e.g. in neuroscience illustrate – Multiple data sources, of different types • Visual images, quantitative data, secondary data – Storage devices – Multiple analytic tools • Some requiring grid power – Supporting complex scholarly communication • Different communities do things differently, eg in terms of file types, tools used Nov-13
  6. 6. Mandating good RDM • Funders’ mandates Value – Research Councils UK Common Principles on Data Policy: – EPSRC principles and expectations: /Pages/default.aspx • Institutional policies – DCC list, Nov-13 Learning material produced by RDMRose
  7. 7. Force field analysis of RDM Compliance Other priorities Good research practice Data storage and security Open access Data preservation Nov-13 Nature of data Good Research Data Management practices Academic culture & lack of reuse culture Lack of RDM knowledge & skills Legal, ethical & commercial exceptions You will want to think about the differing strengths of these forces in your context
  8. 8. 2. WHAT IS THE POTENTIAL LIBRARY ROLE IN RDM? Nov-13 Learning material produced by RDMRose
  9. 9. Why do librarians have something to contribute? • Open access leadership role • Knowledge of relevant information management principles: resource discovery, collection development, metadata skills and practices, licensing/copyright • Liaison, negotiation skills and contacts with academics • Established LIS networks for sharing best practice across the profession
  10. 10. Areas where libraries can contribute to RDM • Policy • Teaching appropriate literacies to PIs and early career researchers, PGR and taught students • Advisory services on RDM; web sites – Awareness of data for reuse; data citation practices; copyright and licensing of data • Signposting • Auditing/ asset review of data sets researchers have • Data curation capacity, e.g. appraisal and collection management policy, metadata creation/advice • Specialist roles in data analysis Involving many library teams: liaison team, metadata specialists, systems team… perhaps embedded roles • In collaboration with other professional services such as computer services, research office and archives/records management staff • In collaboration with researchers and research administrators • In collaboration with other stakeholders, internal and external Cox AM, Verbaan E and Sen B (2012) Upskilling liaison librarians for research data management. Ariadne 70. Available at: (accessed 10 April 2013).
  11. 11. Extra-Institutional Stakeholders Institutional Stakeholders PVC research Department Perspectives on RDM Other Researchers In the discipline Computing services Researchers In other disciplines Research Project Commercial Partners and Customers The Researcher Research Office Data repository manager Library Other HEIs Human resources Records unit and university archive Funding councils The public and wider Society Individual professional perspective
  12. 12. 3. WHAT ARE UK LIBRARIES DOING AND PLANNING TO DO? Nov-13 Learning material produced by RDMRose
  13. 13. RDM in UK HEI libraries survey results • 83 (c 50%) UK HEIs responded to our survey (with Stephen Pinfield) conducted in November 2012 [paper available from JOLIS OnlineFirst doi:10.1177/0961000613492542 or from WRRO ] • For an international comparison see Corrall et al. (2013) • Take home finding: Low level of service development; high priority for next 3 years
  14. 14. Current RDM services Few welldeveloped or extensive services currently being offered by libraries but some basic services
  15. 15. Priorities for the next 3 years Libraries see RDM services as a priority, with a particular emphasis on advisory, policy support and training services
  16. 16. Rank by current activity Open access and policy 1 Copyright 2 Data citation 3 Awareness of reusable sources 4 External data sources 5 Early career awareness 6 PGR training 7 Advisory service 8 Licensing 9 RDM plan advice 10 Web portal 11 Data repository 12 Metadata 13 Audit RDM 14 Data analysis 15 PGT training 16 Data impact 17 UG training 18 Rank by top future priority 1 8 7 5 11 3 3 2 14 11 9 5 10 13 17 15 15 18
  17. 17. Survey results: challenges • “The skill set of the library workforce, the costs of RDM and the difficult economic climate.” • “Capacity and workload in a context of shrinking resources”
  18. 18. Challenges • Librarians are already over-taxed with roles; they operate in a highly dynamic context; organisational change (e.g. embedding) and multi-professional services • Its part of a fundamental shift to an inside out library • Attitudes needed to operate in fluid, changeable context are different • They often do not have personal experience of research • Its non trivial to translate library IM skills to research data issues (eg learning about metadata for data) • Will researchers look to libraries for this support? “Being taken seriously” • The complexity and scale of issues • Resources, infrastructure, management structures have yet to be created in most institutions
  19. 19. What librarians need… • Confidence raising… demystification of a complex social world • Increased knowledge and competencies • A change of identity – ability to take risks, operate in undefined contexts • Prompts to get started with RDM, rather than waiting till policy or infrastructure is clear
  20. 20. Where libraries are starting with RDM • Collaborate with researchers (Garritano and Carlson (2009) at Purdue) • Create a web site with generic advice for all researchers • Use the 23 things model to encourage library staff to find the answers to key questions ( /the-holistic-librarian-open-for-business/ ) • Perform a Data Asset Framework (DAF) survey to explore what data the institution has and how it is managed • Seek representation on faculty and departmental research committees Nov-13 Learning material produced by RDMRose
  21. 21. 4. LEARNING MORE Nov-13 Learning material produced by RDMRose
  22. 22. Key UK resources for further learning • Pryor, G. (2012). Managing Research Data. London: Facet. contains chapters on key aspects, including an excellent overview by the editor and a chapter by Sheila Corrall on librarians’ roles in RDM. • Digital Curation Centre (DCC), – Jones, Pryor and White (2013) explains the issues in setting up RDM service, • JISC Managing Research Data programme of research, • Auckland (2012) sets challenge of RDM in wider context of need to support research more generally, • RDMRose Nov-13 Learning material produced by RDMRose
  23. 23. The URL… An Open Educational Resource on RDM tailored for information professionals
  24. 24. How can you use the learning materials? • Gain a systematic grounding in RDM, through self-directed CPD • Undertake targeted learning about an RDM topic that is key for your role • Reuse material or ideas for teaching your library colleagues and others – join an ongoing informal RDMRose user group • Come to Sheffield to take RDM as a module on one of our Masters courses
  25. 25. MSc Data Science New for 2014 • Data science is an emerging field that seeks to discover and explore new ways of exploiting data to support decisionmaking • There is a “Big Data” explosion with a greater demand than ever before to manage, analyse and use data effectively. • Shortage of trained staff to enable organisations to take advantage of Big Data • Modules include: Data Analysis, Data Mining and visualisation, Research data Management, Business Intelligence, Information Storage and Retrieval
  26. 26. CLOSING THOUGHTS Nov-13 Learning material produced by RDMRose
  27. 27. RDM as a “social mess”/ “wicked problem” • Different (perhaps incommensurable) views of the problem and contradictory solutions • The problem is linked to other problems • Cultural, economic and other constraints on solutions • Lack of information about current state of affairs • Numerous possible intervention points • Considerable uncertainty, ambiguity and risk Rittel and Webber (1973); Horn and Weber (2007) Nov-13 • Implies a different way of operating • How well is IM able to deal with these types of problems? • In a globalised world this type of problem is increasing
  28. 28. Leadership in wicked problem spaces Leadership style: a bricolage • Relationships not structures • Reflection not reaction • Positive deviance not negative acquiescence • Negative capability • Constructive dissent not destructive consent • Collective intelligence not individual genius • Community of fate not a fatalist community • Empathy not egotism Grint (2008) Nov-13
  29. 29. Design thinking (not so clumsy!) A type of creative, problem solution orientated thinking, that requires: But does this fit • Empathy information • Integrative thinking professionals’ mind • Optimism sets and attitudes? (Rylander 2009) • Experimentalism • Collaboration Is it at odds with (Brown 2008) professionalisation? Nov-13
  30. 30. The clumsy librarian • We cannot hope for elegant solutions, they fit ordinary problems • Wicked problems need clumsy solutions and organisations – Have a egalitarian focus on building consensus, a hierarchical stress on role of experts, an individualist trust in competition and a fatalistic wait and see attitude • “Why librarians should be clumsy with research data” icleID=92231 Nov-13 Learning material produced by RDMRose
  31. 31. The clumsy curriculum • Research based learning – e.g. going and talking to researchers • Case study work – e.g. group work around a complex scenario of imaginary but realistic institutional context, stakeholder positions and conflicts over RDM – Need to add “prototyping” element Nov-13
  32. 32. References • • • • Corrall, S., Kennan, M.A. and Afzal, W. (2013), “Bibliometrics and research data management: Emerging trends in library research support services”, Library Trends, 61 (3), pp.636-674. Cox AM, Verbaan E and Sen B (2012) Upskilling liaison librarians for research data management. Ariadne 70. Available at: (accessed 10 November 2013). Cox, AM and Pinfield, S. (2013) Research data management and libraries: Current activities and future priorities, Journal of Library and Information Sciene Duffy, S. (2013). Managing research data in an open access world. Presentation to RLUK members day, Exeter April 2013, • Garritano, J.R. and Carlson, J.R. (2009). A subject librarian’s guide to collaborating on e-Science projects, Issues in Science and Technology Librarianship, Spring No. 57. Available at • RIN. (2009). Patterns of information use and exchange : case studies of researchers in the life sciences. London. Retrieved from Nov-13