RDM for librarians

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

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

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?

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

What are research data?

All manner of things produced
in the course of research

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)

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 …

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

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

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

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

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

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

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

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

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

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?

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

Which funders require a DMP?

www.dcc.ac.uk/resources/policy-and-legal/ overview-funders-data-policies

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

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

Exercise: My DMP - a satire

 Read through the satirical DMP

 Highlight examples of bad practice

 Suggest alternative methods / approaches


My Data Management Plan – a satire, Dr C. Titus Brown
http://ivory.idyll.org/blog/data-management.html

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

Help from the DCC

https://dmponline.dcc.ac.uk

www.dcc.ac.uk/resources/how-guides/develop-data-plan

How DMPonline works
Create a plan
based on
relevant
funder /
institutional
templates...

...and then
answer the
questions
using the
guidance
provided

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)

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

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!

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

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.”

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

Constraints on data sharing Possible solutions / approaches

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

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

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

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

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

Exercise: skills to support RDM
 Based on the activities we discussed earlier, consider who
may have relevant skills or expertise to share.

Activity Library and IT Services Other professional
Learning Services services
Copyright
Data citation
Information
literacy
Data storage
Digital preservation
Metadata
...

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

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

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

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

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

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

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

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...

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

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?


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 

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?

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

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