Research Data Management & Libraries: Relationships, Activities, Drivers & Influences Stephen Pinfield Information School, University of Sheffield ‘Supporting the activities of your research community – issues and initiatives’, 3 December 2014, Dublin

Overview Research support and libraries Data and research data management RDM challenges: RDM as ‘wicked’ problem Modelling institutional RDM: components, stakeholders, drivers, influences Leadership Boundaries, collaboration and competition Skills

Acknowledgments Dr Andrew Cox Dr Barbara Sen Dr Jen Smith Dr Eddy Verbaan

Identify research question/ issue Design research approach/ methodology Identify and assemble resources/funding required Gather/ create data/ sources Analyse data/ sources Interpret data/ sources Communicate results Consult other communicated research Evaluate effectiveness of research Research: An investigation undertaken to acquire knowledge and understanding The Research Cycle

Provide access to published content and support its use Provide access to tools and expertise Provide access to funding information Manage, describe, preserve, share data and other content Provide data/ sources Provide a ‘venue’ for some research activity (physical and virtual) Assist research communication activity (systems and support) – e.g. open access Identify research question/ issue Design research approach/ methodology Identify and assemble resources/funding required Gather/ create data/ sources Analyse data/ sources Interpret data/ sources Communicate results Consult other communicated research Evaluate effectiveness of research Research: An investigation undertaken to acquire knowledge and understanding The Research Cycle and the Library

Strategic Shift (From: Dempsey, Malpas, & Lavoie, 2014) From ‘outside in’ To ‘inside out’

‘Data’ “Data are facts, numbers, letters, and symbols that describe an object, idea, condition, situation, or other factors” (US National Research Council, 1999) Data: “alleged evidence” (Buckland, 1991) “Data may exist only in the eye of the beholder” (Borgman, 2012) – community defined Data: Mass noun, sing. “Facts and statistics collected together for reference or analysis” (OED Online)

Research Data Management Research data management: “the organisation of data, from its entry to the research cycle through to the dissemination and archiving of valuable results” (Whyte & Tedds, 2011) RDM “consists of a number of different activities and processes associated with the data lifecycle, involving the design and creation of data, storage, security, preservation, retrieval, sharing, and reuse, all taking into account technical capabilities, ethical considerations, legal issues and governance frameworks” (Cox & Pinfield, 2014)

Data Challenges Variety Velocity Volume 3 V’s of Data (Laney, 2001)

6 V’s of Data Data Challenges Variety Validity Velocity Volume Value Visibility (Laney, 2001; and others)

RDM as a ‘Wicked’ Problem Rittel & Webber (1973) 1.No agreed formulation of the problem 2.Things keep changing 3.No right answer 4.No test to see if a solution will/has worked 5.No gradual solutions possible 6.Not list of comprehensive solutions 7.Problem unique 8.Wicked problems derive from other problems 9.Problem and solutions can be seen from different perspectives 10.Problem and solutions have direct aff ect on people Horn & Weber (2007) 11.Multiple value conflicts in the problem 12.Multiple constraints on solutions 13.Resistance to change 14.Data to describe the problem is often missing 15.Multiple intervention points 16.Consequences of intervention difficult to imagine RDM has many of the characteristics of a wicked problem (Cox, Pinfield, & Smith, 2014)

Wicked Problems and Clumsy Solutions “The point of the distinction between tame and wicked problems is that if we know a problem is wicked we operate differently…Unlike the elegant solution possible for a clearly definable problem, we can only hope for a clumsy solution to a wicked problem, one that partly satisfies different stakeholders.” “Nevertheless, in some senses it does not feel as fundamentally intractable as a truly wicked problem or so critical…” (Cox, Pinfield, & Smith, 2014)

Drivers: Why? Acceptance Cultures Demand Incentives Roles Governance Politics Resources Projects Skills Communications Context Influencing Factors: How? LibraryIT Services Academic Departments Senior University Managers Research Support Services Other Support Services Stakeholders: Who? Researchers: Arts and Humanities Disciplines Researchers: Social Sciences Disciplines Researchers: Science Disciplines Researchers: Engineering Disciplines Researchers: Medicine and Health Disciplines Researchers: Multi- Disciplinary Collaborations Strategies Policies Processes Technologies Guidelines Services RDM Programme Components: What? (Pinfield, Cox, & Smith, 2014)

Stakeholders: Who? Strategies Policies Processes Technologie s Guidelines Services Acceptance Demand Incentives Roles Cultures Governance Politics Resources Projects Skills Communications Setting Drivers: Why? RDM Programme Components: What? Influencing Factors: How?

Strategies Policies Processes Technologies Guidelines Services RDM Programme Components: What?

Drivers: Why? Strategies Policies Processes Technologies Guidelines Services RDM Programme Components: What?

Drivers: Why? Stakeholders: Who? Strategies Policies Processes Technologies Guidelines Services RDM Programme Components: What?

Drivers: Why? LibraryIT Services Academic Departments Senior University Managers Research Support Services Other Support Services Stakeholders: Who? Researchers: Arts and Humanities Disciplines Researchers: Social Sciences Disciplines Researchers: Science Disciplines Researchers: Engineering Disciplines Researchers: Medicine and Health Disciplines Researchers: Multi- Disciplinary Collaborations Acceptance Cultures Demand Incentives Roles Governance Politics Resources Projects Skills Communications Context Influencing Factors: How? Strategies Policies Processes Technologies Guidelines Services RDM Programme Components: What?

Leadership Leadership Improvisation (Grint, 2008) 1.Questions not answers 2.Relationships not structures 3.Reflection not reaction 4.Positive deviance not negative acquiescence 5.Negative capability 6.Constructive dissent not destructive consent 7.Collective intelligence not individual genius 8.Community of fate not a fatalist community 9.Empathy not egotism Design Thinking (Brown, 2008) Empathy Integrative thinking Optimism Experimentalism Collaboration

Competition and/or Collaboration? RDM infrastructure components Lead department RDM policy and strategyLibrary Data management planningResearch office Managing active dataIT Services Data selection and handover? Data repositoriesIT services, Library, Research office Data cataloguesLibrary, IT services, Research office Guidance, training and supportLibrary, Research office, IT services Case study: Division of likely roles of the three main professional services in RDM, using the DCC’s components of an RDM infrastructure headings (Verbaan & Cox, 2014)

Boundaries and the “Third Space” Academic Professional Service “Third Space” (Based on Whitchurch, 2013)

Identity ‘dispositions’Characteristics ‘Bounded professionals’ (voluntary or involuntary) Work within clear structural boundaries (e.g. specialist function, job description) ‘Cross-boundary professionals’ Actively use boundaries and cross-boundary knowledge for strategic advantage and institutional capacity building ‘Unbounded professionals’ Lack of consciousness of boundaries; focus on broadly-based projects across the university, and contribute to institutional development ‘Blended professionals’ Dedicated appointments spanning professional and academic domains “Dispositions” of Professional Staff (Whitchurch, 2013)

Boundaries, the “Third Space” and RDM AcademicLibrary RDM “Third Space” Research Office IT Services (Based on Whitchurch, 2013) ?

Other Collaborations Consortial Regional National International Professional

Skills

Questions & Comments

References Borgman, C. L. (2012). The conundrum of sharing research data. Journal of the American Society for Information Science and Technology, 63(6), 1059–1078. doi: /asi Brown, T. (2008). Design thinking. Harvard Business Review, 86(6), 84. Cox, A. M., & Pinfield, S. (2014). Research data management and libraries: Current activities and future priorities. Journal of Librarianship and Information Science, 46(4), doi: / Cox, A. M., Pinfield, S., & Smith, J. (2014). Moving a brick building: UK libraries coping with research data management as a “wicked” problem. Journal of Librarianship and Information Science, (Pre-published April 2014). doi: / Dempsey, L., Malpas, C., & Lavoie, B. (2014). Collection directions: The evolution of library collections and collecting. Portal: Libraries and the Academy, 14(3), 393–423. doi: /pla Grint, K. (2008). Wicked problems and clumsy solutions: The role of leadership. Clinical Leader, 1(2), 11–15. Horn, R., & Weber, R. (2007). New tools for resolving wicked problems: Mess mapping and resolution mapping processes. Watertown, MA: Strategy Kinetics LLC. Retrieved from Problems_Exec_Summary.pdf

References Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. Stamford, CT: META Group. Retrieved from laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity- and-Variety.pdf Pinfield, S., Cox, A. M., & Smith, J. (2014). Research data management and libraries: Relationships, activities, drivers and influences. PLOS ONE, (In press). Rittel, H., & Webber, M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4(2), 155–169. Verbaan, E., & Cox, A. M. (2014). Occupational sub-cultures, jurisdictional struggle and third space: Theorising professional service responses to research data management. The Journal of Academic Librarianship. doi: /j.acalib Whitchurch, C. (2013). Reconstructing identities in higher education: The rise of third space professionals. London: Routledge. Whyte, A., & Tedds, J. (2011). Making the case for research data management. Edinburgh: Digital Curation Centre. Retrieved from