Presentation given at the University of Northampton in a 3 hour training session for academic liaison librarians.

1. Research Data
Management
for librarians
Sarah Jones & Marieke Guy
Digital Curation Centre
Miggie Pickton, University of Northampton

2. About this course
 Short presentations with exercises and discussion
 Five main sections
― Research data and RDM (30 mins)
― Data Management Planning (30 mins)
― Data sharing (20 mins)
― Skills (30 mins)
― RDM at Northampton (30 mins)
 Coffee break halfway through, after data sharing

3. Introductions
Introduce yourself and offer a reflection on the questions:
 What is your understanding of research?
 Do you know anything about data management?
 What do you want to find out today?
 Do you see a role for librarians in supporting RDM?

4. Research data and RDM

5. Exercise: What are research data?
 In pairs, list as many types of data as you can, focusing
(if appropriate) on the subject areas you support
 You have 5 minutes

6. What are research data?
All manner of things produced
in the course of research

7. Defining research data
 Research data are collected, observed or created, for
the purposes of analysis to produce and validate
original research results
 Both analogue and digital materials are 'data'
 Lab notebooks and software may be classed as 'data'
 Digital data can be:
― created in a digital form ('born digital')
― converted to a digital form (digitised)

8. Types of research data
 Instrument measurements
 Experimental observations
 Still images, video and audio
 Text documents, spreadsheets, databases
 Quantitative data (e.g. household survey data)
 Survey results & interview transcripts
 Simulation data, models & software
 Slides, artefacts, specimens, samples
 Sketches, diaries, lab notebooks …

9. What is data management?
“the active management and appraisal of data over
the lifecycle of scholarly and scientific interest”
Digital Curation Centre

10. What is involved in RDM?
 Data Management Planning
 Creating data
 Documenting data
Create
 Accessing / using data
Preserve Document
 Storage and backup
 Sharing data Share Use
 Preserving data Store

11. RDM principles and advice
to share with researchers
n.b. Data Management Planning and Data Sharing are
covered in separate sections
See in particular:
UK Data Archive, Managing and sharing data: best practice for researchers
http://data-archive.ac.uk/media/2894/managingsharing.pdf

12. Data creation
 Decide what data will be created and how - this should
be communicated to the whole research team
 Develop procedures for consistency and data quality
 Choose appropriate software and formats - some are
better for long-term preservation and reuse
 Ensure consent forms, licences and partnership
agreements don’t limit options to share data if desired

13. Documentation
 Collect together all the information users would
need to understand and reuse the data
 Create metadata at the time - it’s hard to do later
 Use standards where possible
 Name, structure and version files clearly

14. Access and use
 Restrict access to those who need to read/edit data
 Consider the data security implications or where you
store data and from which devices you access files
 Choose appropriate methods to transfer / share data
― filestores & encrypted media rather than email & Dropbox

15. Storage and backup
 Use managed services where possible e.g. University
filestores rather than local or external hard drives
 Ask the local IT team for advice
 3… 2… 1… backup!
― at least 3 copies of a file
― on at least 2 different media
― with at least 1 offsite

16. Data selection
 It’s not possible to keep everything. Select based on:
― What has to be kept e.g. data underlying publications
― What legally must be destroyed
― What can’t be recreated e.g. environmental recordings
― What is potentially useful to others
― The scientific or historical value
― ...
How to select and appraise research data:
www.dcc.ac.uk/resources/how-guides/appraise-select-research-data

17. Data preservation
 Be aware of requirements to preserve data
 Consult and work with experts in this field
 Use available subject repositories, data centres and
structured databases
― http://databib.org

18. Data Management Planning

19. Data Management Planning
DMPs are written at the start of a project to define:
 What data will be collected or created?
 How the data will be documented and described?
 Where the data will be stored?
 Who will be responsible for data security and backup?
 Which data will be shared and/or preserved?
 How the data will be shared and with whom?

20. Why develop a DMP?
DMPs are often submitted with grant applications, but
are useful whenever researchers are creating data.
They can help researchers to:
 Make informed decisions to anticipate & avoid problems
 Avoid duplication, data loss and security breaches
 Develop procedures early on for consistency
 Ensure data are accurate, complete, reliable and secure

21. Which funders require a DMP?
www.dcc.ac.uk/resources/policy-and-legal/ overview-funders-data-policies

22. What do research funders want?
 A brief plan submitted in grant applications, and in the
case of NERC, a more detailed plan once funded
 1-3 sides of A4 as attachment or a section in Je-S form
 Typically a prose statement covering suggested themes
 Outline data management and sharing plans, justifying
decisions and any limitations

23. Five common themes / questions
 Description of data to be collected / created
(i.e. content, type, format, volume...)
 Standards / methodologies for data collection & management
 Ethics and Intellectual Property
(highlight any restrictions on data sharing e.g. embargoes, confidentiality)
 Plans for data sharing and access
(i.e. how, when, to whom)
 Strategy for long-term preservation

24. Exercise: My DMP - a satire
 Read through the satirical DMP
 Highlight examples of bad practice
 Suggest alternative methods / approaches
 You have 15 minutes
My Data Management Plan – a satire, Dr C. Titus Brown
http://ivory.idyll.org/blog/data-management.html

25. A useful framework to get started
Think about why
the questions are
being asked
Look at examples
to get an idea of
what to include
www.icpsr.umich.edu/icpsrweb/content/datamanagement/dmp/framework.html

26. Help from the DCC
https://dmponline.dcc.ac.uk
www.dcc.ac.uk/resources/how-guides/develop-data-plan

27. How DMPonline works
Create a plan
based on
relevant
funder /
institutional
templates...
...and then
answer the
questions
using the
guidance
provided

28. Supporting researchers with DMPs
Various types of support could be provided by libraries:
 Guidelines and templates on what to include in plans
 Example answers, guidance and links to local support
 A library of successful DMPs to reuse
 Training courses and guidance websites
 Tailored consultancy services
 Online tools (e.g. customised DMPonline)

29. Tips to share: writing DMPs
 Keep it simple, short and specific
 Seek advice - consult and collaborate
 Base plans on available skills and support
 Make sure implementation is feasible
 Justify any resources or restrictions needed
Also see: http://www.youtube.com/watch?v=7OJtiA53-Fk

30. Data sharing

31. What is data sharing?
“… the practice of making data used for scholarly
research available to others.” [Wikipedia]
Who’s involved?
 the data sharer
 the data repository
 the secondary data user
 support staff!

32. Reasons to share data
BENEFITS DRIVERS
 Avoid duplication  Public expectations
 Scientific integrity  Government agenda
 More collaboration  RCUK Data Policy
 Better research
― www.rcuk.ac.uk/research/Pages/
DataPolicy.aspx
 Increased citation
 Northampton RDM policy
69% increase shown in study ― http://tiny.cc/Research-Data-
(Piwowar, 2007, PLoS) Policy

33. The expectation of public access
The RCUK Common Principles state that:
“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 that
does not harm intellectual property.”

34. Exercise: barriers to data sharing
 Briefly list some reasons why certain data can’t be
shared and consider whether any actions could be
taken to reduce or overcome these restrictions
 You have 10 minutes
Constraints on data sharing Possible solutions / approaches

35. Managing restrictions on sharing
Ethics
Balance data protection with data sharing
 Informed consent – cover current and future use
 Confidentiality – is anonymisation appropriate?
 Access control – who, what, when?
IPR
 Clarify copyright before research starts
 Consider licensing options e.g. Creative Commons

36. Select formats for data sharing
It’s better to use formats that are:
 Unencrypted
 Uncompressed
 Non-proprietary/patent-encumbered
Research360
 Open, documented standard
 Standard representation (ASCII, Unicode)
Type Recommended Avoid for data sharing
Tabular data CSV, TSV, SPSS portable Excel
Text Plain text, HTML, RTF Word
PDF/A only if layout matters
Media Container: MP4, Ogg Quicktime
Codec: Theora, Dirac, FLAC H264
Images TIFF, JPEG2000, PNG GIF, JPG
Structured data XML, RDF RDBMS
Further examples: http://www.data-archive.ac.uk/create-manage/format/formats-table

37. How to share research data
 Use appropriate repositories
― http://databib.org
 License the data so it is clear how it can be reused
― www.dcc.ac.uk/resources/how-guides/license-research-data
 Make sure it’s clear how to cite the data
― http://www.dcc.ac.uk/resources/how-guides/cite-datasets

38. Skills

39. How are libraries engaging in RDM?
The library is leading on most DCC institutional engagements.
They are involved in:
 defining the institutional strategy
 developing RDM policy
 delivering training courses
 helping researchers to write DMPs
 advising on data sharing and citation
 setting up data repositories
Library
 ...
Research
www.dcc.ac.uk/community/institutional-engagements Office
IT

40. Why should libraries support RDM?
RDM requires the input of all support services, but
libraries are taking the lead in the UK – why?
― existing data and open access leadership roles
― often run publication repositories
― have good relationships with researchers
― proven liaison and negotiation skills
― knowledge of information management, metadata etc
― highly relevant skill set

41. Exercise: skills to support RDM
 Based on the activities we discussed earlier, consider who
may have relevant skills or expertise to share.
 You have 15 minutes
Activity Library and IT Services Other professional
Learning Services services
Copyright
Data citation
Information
literacy
Data storage
Digital preservation
Metadata
...

42. Possible Library RDM roles
 Leading on local (institutional) data policy
 Bringing data into undergraduate research-based learning
 Teaching data literacy to postgraduate students
 Developing researcher data awareness
 Providing advice, e.g. on writing DMPs or advice on RDM within a project
 Explaining the impact of sharing data, and how to cite data
 Signposting who in the Uni to consult in relation to a particular question
 Auditing to identify data sets for archiving or RDM needs
 Developing and managing access to data collections
 Documenting what datasets an institution has
 Developing local data curation capacity
RDMRose Lite
 Promoting data reuse by making known what is available

43. An exciting opportunity
“Researchers need help to manage
their data. This is a really exciting
opportunity for libraries….”
Liz Lyon, VALA 2012
 Leadership
 Providing tools and support
 Advocacy and training
 Developing data informatics capacity & capability

44. Potential challenges
 Librarians are already over-taxed!
― Other challenges in supporting research (Auckland, 2012)
― Getting up-to-speed and keeping up-to-date
 How deep is our understanding of research, especially
scientific research and our level of subject knowledge?
 Translating library practices to research data issues
 Will researchers look to libraries for this support?
RDMRose Lite
 Still need to resource and develop infrastructure

45. RDM at Northampton

46. RDM drivers at Northampton
 REF: research environment; impact
 Institutional reputation
 Pressure from funders: government; RCUK; EPSRC
(sharing mandates)
 Publisher demands: evidence to support published work
 Legislative requirements: FOI/EIR requests; Data
Protection
 Long term (open) access: reuse and repurpose
 Good research practice

47. A (very) brief history of RDM at Northampton
May-June
• First research data (DAF) project aims to establish researchers’ current RDM practices
2010
• DAF project report presented to University Research Committee (URC)
October
2010
• URC working group convened to develop research data policy
Jan-June
• Research Data Policy proposed, refined and approved by URC
2011
• Research data roadmap created in response to EPSRC requirements
April 2012 • DCC ‘engagement' starts
• RDM training and guidance for researchers – led by DCC, supported by LLS
Ongoing • Piloting of TUNDRA2 for research data storage and access

48. Northampton RDM policy
 Adopt the RCUK code of good practice
 Write and follow a Data Management Plan
 Make data accessible wherever possible
 Deposit in a repository for preservation
www.northampton.ac.uk/info/20283/academic-
research/1606/research-data-policy

49. UoN research data roadmap
 Maps current and planned practice to EPSRC expectations
 Covers: awareness of regulatory environment; connection with
published papers; access to datasets; use of metadata; and
data curation
 Coverage extended to all subject areas to encourage good data
management practice
and ensure equality of
provision
 Roadmap approved by
R&EC in April 2012
 But extra resources still
need approval by UET

50. DCC Engagement
 So far DCC staff have run training sessions on:
― Managing your PhD data (for research students)
― Managing data through the research lifecycle (Business)
― Meeting funders’ requirements for RDM (Social Sciences)
 And provided guidance:
― Creation of a DMPonline template for the University of Northampton, with
attached guidelines
― Development of a guide to meeting ESRC data management planning
requirements (in conjunction with John Horton)
 We have also run one-to-one RDM clinics for researchers
 Still to come:
― Further training for Schools
― Series of posts on the Research Support Hub
― Further support for research data storage...

51. TUNDRA2 for research data
 The University (led by Phil Oakman) is rolling out TUNDRA 2
― open content management system
― to store, manage and preserve files
― facility to share internally and externally
 Jane Callaghan & colleagues are piloting this for managing
research data in her big European project
 Phil hopes to develop a generic template in TUNDRA2 that
will serve other research projects
 Let us know if you know of others who would like to be
involved

52. Exercise: supporting RDM at Northampton?
 In small groups, discuss which activities you think
should fall within your role and which shouldn’t.
 Do you feel confident to support RDM?
 How would you like to see things develop?
 You have 15 minutes

53. Conclusion

54. Summary
 In the light of external drivers, researchers at
Northampton need support for RDM
 LLS has a key role in shaping services for researchers
in this area
 LLS staff have an opportunity to apply their skills in a
new and exciting way 

55. Feedback
 Has the event met your expectations?
― If not, what would you have liked to see more / less of?
 Was the content useful?
 Did you like the mix of exercises?

56. Acknowledgement
Ideas and content have been taken from various courses:
― Skills matrix, ADMIRe project, University of Nottingham
http://admire.jiscinvolve.org/wp/2012/09/18/rdmnottingham-training-event
― DIY Training Kit for Librarians, University of Edinburgh
http://datalib.edina.ac.uk/mantra/libtraining.html
― Managing your research data, Research360, University of Bath
http://opus.bath.ac.uk/32296
― RDMRose Lite, University of Sheffield
http://rdmrose.group.shef.ac.uk/?page_id=364
― RoaDMaP training materials, University of Leeds
http://library.leeds.ac.uk/roadmap-project-outputs
― SupportDM modules, University of East London
http://www.uel.ac.uk/trad/outputs/resources