Research Data Management &

Libraries: Work in Progress

Stephen Pinfield

Information School,

University of Sheffield

Bodleian Libraries Conference: Adapting for the Future:

Developing our Professions and Services, 21 July 2015

Overview

1. Research support and libraries

2. Data and research data management

3. RDM challenges: RDM as ‘wicked’ problem

4. Modelling institutional RDM: components,

stakeholders, drivers, influences

5. Leadership and libraries

6. Boundaries, collaboration and competition

7. Roles and skills

Acknowledgments

University of Sheffield,

Information School

Andrew Cox

Barbara Sen

Jen Smith

Eddy Verbaan

University of Sheffield,

University Library

Martin Lewis

Charles Sturt University,

Australia

Mary Anne Kennan

University of Pittsburgh,

USA

Liz Lyon

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)

http://www.dcc.ac.uk/sites/default/files/documents/publications/DCCLifecycle.pdf

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 affect 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)

Storage

Security

Preservation

Compliance

Quality

Sharing

Jurisdiction

Drivers: Why?

Acceptance

Cultures

Demand

Incentives

Roles

Governance

Politics

Resources

Projects

Skills

Communications

Context

Influencing Factors: How?

Library IT 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?

Storage

Security

Preservation

Compliance

Quality

Sharing

Jurisdiction

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?

Storage

Security

Preservation

Compliance

Quality

Sharing

Jurisdiction

Drivers: Why?

Strategies

Policies

Processes Technologies

Guidelines

Services

RDM Programme Components: What?

Storage

Security

Preservation

Compliance

Quality

Sharing

Jurisdiction

Drivers: Why?

Library IT 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?

Storage

Security

Preservation

Compliance

Quality

Sharing

Jurisdiction

Drivers: Why?

Library IT 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?

Leading on Policy Development

From late 2014; N=170; Australia 34/39; Canada 17/74; Germany 8/48;

Ireland 7/8; Netherlands 12/16; New Zealand 7/7; UK 85/169

(Cox, Kennan, Lyon & Pinfield, Forthcoming)

“Does your

institution have a

formal research

data management

(RDM) policy in

place which

covers issues

such as retention,

storage and

sharing?”

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

Support Services Roles

RDM infrastructure

components

Lead department

RDM policy and strategy Library

Data management planning Research office

Managing active data IT Services

Data selection and handover ?

Data repositories IT services, Library, Research office

Data catalogues Library, IT services, Research office

Guidance, training and support Library, 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)

Support Services Roles

Library

Research Office

IT

(Based on analysis

by Martin Lewis)

Repository management - Metadata -

Data literacy - Date of publication -

Data service landscape - Intellectual property - Digital preservation -

Data storage - Data transmission -

Data migration - Data security - Authorisation /

authentication -

- Research funders - Research costing - Research policy - Research integrity - IP, patents,

commercialisation

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

Academic Library

RDM

“Third

Space”

Research

Office

IT

Services

(Based on

Whitchurch, 2013)

?

Other Collaborations

Consortial

Regional

National

International

Professional

Skill Development Needs in Libraries

UK libraries’ assessments of their skills gaps

(Cox, Kennan, Lyon & Pinfield, Forthcoming)

Skills

Questions & Comments

S.Pinfield@Sheffield.ac.uk

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:10.1002/asi.22634

• Brown, T. (2008). Design thinking. Harvard Business Review, 86(6), 84.

• Cox, A. M., Kennan, M.A., Lyon, L., & Pinfield, S. (Forthcoming). Mapping the maturity of research

data management in libraries: An international study exploring leadership, service development,

and workforce capacity and capability

• Cox, A. M., & Pinfield, S. (2014). Research data management and libraries: Current activities and

future priorities. Journal of Librarianship and Information Science, 46(4), 299-316.

doi:10.1177/0961000613492542

• 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:10.1177/0961000614533717

• 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:10.1353/pla.2014.0013

• 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

http://robertweber.typepad.com/strategykinetics/New_Tools_For_Resolving_Wicked_Problems_E

xec_Summary.pdf

References

• Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. Stamford,

CT: META Group. Retrieved from http://blogs.gartner.com/doug-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, 9(12), e114734.

doi:10.1371/journal.pone.0114734

• 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:10.1016/j.acalib.2014.02.008

• 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 http://www.dcc.ac.uk/webfm_send/487