RDM Programme at University of Edinburgh

RDM PROGRAMME @ EDINBURGH
Stuart Macdonald
RDM Service Coordinator
University of Edinburgh
stuart.macdonald@ed.ac.uk
RDM Workshop, University of Tartu, Estonia, 24 October 2014

• Background
o EDINA & Data Library
• Defining research data
• Research data management
o benefits, drivers, funders
• RDM programme
o policy and implementation
• RDM services and support
o RDM planning
o data stewardship
o awareness raising and training
• JISC

BACKGROUND
• EDINA and University Data Library (EDL) together are a
division within Information Services (IS) of the University of
Edinburgh.
• EDINA is a Jisc-funded National Data Centre providing
national online resources for education and research.
• The Data Library assists Edinburgh University users in the
discovery, access, use and management of research
datasets.
Data Library Services: http://www.ed.ac.uk/is/data-library
EDINA: http://edina.ac.uk/

EDINA – Jisc-designated centre for digital expertise
& online service delivery
• Mission statement: “.. [to] develop and deliver online services and
digital infrastructure for UK research and education ...”
• Networked access to a range of online resources for UK FE and
HE
• Services free at the point of use for staff and students in
learning, teaching and research through institutional
subscription
• Focus on service but also undertake R&D (projects  services)
• delivers about 20 online services
• 5 - 8 major projects (incl. services in development)
• employs about 80 staff (Edinburgh & St Helens)

DATA LIBRARY
• finding…
• accessing …
• using …
• troubleshooting …
• managing …
Primarily supporting research in the social sciences but not
exclusively so
Building relationships with researchers via postgraduate
teaching activities, research support projects, IS Skills
workshops, Research Data Management training and through
traditional reference interviews.

DEFINING RESEARCH DATA
• Research data are collected, observed or created, for the
purposes of analysis to produce and validate original
research results.
• Research data can be generated for different purposes and
through different processes in a multitude of digital
formats
• Both analogue and digital materials are ‘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 …

RESEARCH DATA MANAGEMENT
• Research data management is caring for, facilitating
access to, preserving and adding value to research
data throughout their lifecycle.
• Data management is one of the essential areas of
responsible conduct of research.
• It provides a framework that supports researchers
and their data throughout the course of their
research and beyond.

ACTIVITIES INVOLVED IN RDM
 Data Management Planning
 Creating data
 Documenting data
 Accessing / using data
 Storage and backup
 Sharing data
 Preserving data

BENEFITS
Managing your data means that you will:
• Meet funder / university / industry requirements.
• Ensure data are accurate, complete, authentic and
reliable – as per good research practice.
• Ensure research integrity and replication.
• Enhance data security & minimise the risk of loss.
• Protect important IPR.
• Increase efficiency - save time & resources.
• Increase impact by sharing data (increase in citations 9
- 30% : Piwowar & Vision 2013)

COMMON THEMES ACROSS FUNDING BODIES
• What data will be created? (format, types, volumes etc)
• What standards and methodologies will you use?
• How will ethics and Intellectual Property be managed?
(highlight any restrictions on data sharing e.g. embargoes,
confidentiality)
• What are the plans for data sharing and access?
• What is the strategy for long-term preservation?

RDM PROGRAMME @ EDINBURGH
- an institutional approach
Edinburgh Data Audit Framework (DAF) Implementation Project
(May – Dec 2008)
A JISC-funded pilot project produced 6 case studies from
research units across the University in identifying research data
assets and assessing their management, using DAF methodology
developed by the Digital Curation Centre.
2 main outcomes:
• Develop university research data management policy
• Develop services & support for RDM (in partnership IS)
DAF Implementation Project: http://ie-repository.jisc.ac.uk/283/

UNIVERSITY OF EDINBURGH RDM POLICY
 University of Edinburgh is one
of the first Universities in UK
to adopt a policy for
managing research data:
http://www.ed.ac.uk/is/rese
arch-data-policy
 The policy was approved by
the University Court on 16
May 2011.
 It’s acknowledged that this is
an aspirational policy and
that implementation will
take some years.

POLICY IMPLEMENTATION
RDM Programme in 3 phases:
• Phase 0: August 2012 – August 2013: Planning phase, with
some pilot activity and early deliverables.
• Phase 1: September 2013 – May 2014: Initial rollout of
primary services.
• Phase 2: June 2014 – May 2015: Continued rollout;
maturation of services.
Full details of the programme is available at:
http://edin.ac/1eE3sav

COMMITTEES
An RDM Policy Implementation Committee was set up by the
Vice Principal Knowledge Management charged with delivering services
that will meet RDM policy objectives:
• Membership from across IS
• Iterate with researchers to ensure services meet the needs of
researchers
The Vice Principal also established a Steering Committee led by
Prof. Peter Clarke with members of Research Committee from the 3
colleges, IS, DCC and Edinburgh Research and Innovation (ERI).
Their role is to:
• Provide oversight to the activity of the Implementation Committee
• Ensure services meet researcher requirements without harming
research competitiveness

RDM SERVICES AND SUPPORT
 Services already in place:
o Data management planning
o Active working file space =
DataStore
o Data publication repository =
DataShare
 Services in development:
o Long term data archive =
DataVault
o Data Asset Register (DAR)
RDM Roadmap
 RDM support: Awareness
raising, training & consultancy http://edin.ac/1u3sKqy

RESEARCH DATA MANAGEMENT PLANNING
Support and services for planning activities that are
performed at the conceptual stage before research
data are collected or created
• Tailored DMP assistance for researchers submitting
research proposals
• Customised instance of DMPonline toolkit for
University of Edinburgh use

WHAT IS A DATA MANAGEMENT PLAN (DMP)?
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?

DMP SUPPORT
• Academic Support Librarians have received RDM training,
including training on writing Data Management Plans.
• Research Administrators staff have received training to provide
support at the grant application stage across the 3 Colleges.
• ERI staff will be receiving RDM training.
• Tailored DMP courses for research staff and PGRs are being
delivered.
• MANTRA also has a module on DMP for self-paced learning.
• General DMP queries can be sent to the IS Helpline who will
direct them as appropriate.

DMPONLINE TOOLKIT
Free and open web-based tool
to help researchers write
plans:
https://dmponline.dcc.ac.uk/
It features:
o Templates based on
different requirements
o Tailored guidance
(disciplinary, funder etc.)
o Customised exports to a
variety of formats
o Ability to share DMPs with
others

TEMPLATES AND GUIDANCE
• Edinburgh University Templates and Guidance are still in
draft.
• Edinburgh University Guidance is provided for those
applying to: AHRC, BBSRC, CRUK, ESRC, MRC, NSF, NERC,
STFC, & Wellcome Trust.
• Edinburgh University Templates are available for
Researchers and PGRs not applying to any of the above.
• Customised Guidance is given for those working at the
Roslin Institute.

DATASTORE
 Facility to store data that are actively used in current research
activities
 Provision: 1.6PB storage initially
 0.5 TB (500GB) per researchers, PGR upwards
 Up to 0.25TB of each allocation can be used to create “shared”
group storage
 Cost of extra storage: £200 per TB per year= 1TB primary storage,
10 days online file history, 60 days backup, DR copy
 Infrastructure in place. Allocation of space devolved to IT
departments of respective Schools overseen by Heads of IT from
each College.

DATA SYNC
• to allow sharing of research data via web interface onto
DataStore data,
• provide drop-box style functionality
• uses open source ‘ownCloud’ technology
• In order for desktop machines to synchronize files with
the ownCloud server:
• desktop clients are available for PCs running Windows, OS X, or
Linux
• Mobile clients also exist for iOS and Android devices.
• Files can also be accessed using a web browser without
any additional software. Any updates to files are pushed
between all devices connected to a user's account.

DATASHARE
 Edinburgh DataShare is the
University data repository for
publishing your research data
openly:
http://datashare.is.ed.ac.uk
 It will help you disseminate
your research, get credit for
your data collection efforts,
and preserve your data for the
long-term.
 It backs up the University
Research Data Management
policy.
 It can help you comply with
funder requirements to
preserve and share your data.

DATA VAULT
 Safe, private, store of data
that is only accessible by the
data creator or their
representative
 Secure storage:
o File security
o Storage security
o Additional security: encryption
 Long term assurance
 Automatic versioning http://datablog.is.ed.ac.uk/2013/12/20/t
hinking-about-a-data-vault

DATA ASSET REGISTER (DAR)
 a catalogue of data assets produced by researchers
working for the University of Edinburgh,
 will be a key component of the University of Edinburgh
Research Data Management (RDM) systems
 will give researchers a single place to record the
existence of data assets they have produced so that they
can be discovered, accessed, and reused as appropriate.
 Paper proposing the adoption of PURE as the University’s
DAR submitted the RDM Steering Committee for approval
(Oct. 2014)
http://datablog.is.ed.ac.uk/2013/12/12/thinking-about-research-data-asset-registers

INTEROPERATION
Systems do not live in isolation,
and become more powerful and
more likely to be used if they are
integrated with each other.
However, the last thing that we
want is to introduce further
systems that need to be fed with
duplicate information.
This means interoperation for
some or all of the components

RDM SUPPORT
Making the most of local support!
• RDM team will work with the Research Administrators in each
School.
• Academic Support Librarians (who represent each of the 22
Schools).
• IT staff in each School.
• ERI staff. They will be receiving RDM training.
• Each School’s Ethics Committee
• Bespoke RDM email address or queries can be sent to the
Helpline who will direct them as appropriate.

COMMUNICATIONS PLANS
There are a number of different groups within the university and outside
with whom we need to communicate our RDM programme.
This will be done through a variety of communication activities.
Target Audiences
1. University of Edinburgh staff need to understand the principles of RDM
and how it is practiced and supported within the University:
• Research active staff
• IS and School/college support staff
• Other university committees and groups (research policy group, library
committee, IT committee, knowledge strategy committee)
2. External collaborators and stakeholders such as funding bodies, Russell
Group, national and international RDM community e.g. RDA, DANS,
ANDS, COAR, DPC, DCC

KEY MESSAGES:
Co-ordinated, Consistent, Coherent
There are three key messages which will need to be tailored and made timely
and relevant to our target audiences.
The core of each message must be maintained to ensure that everyone gains
the same level of understanding.
1. The University is committed to and has invested in RDM
• services, training, support
2. What is meant by Research Data Management?
• definitions, data lifecycle, responsibilities
3. The University is supporting researchers
• encourage good research practice, effect culture change

AWARENESS RAISING
• Introductory sessions on RDM
services and support for research
active and research admin staff in
Schools / Institutes / Research
Centres
• Contact Cuna Ekmekcioglu at
cuna.ekmekcioglu@ed.ac.uk for a
session for your School/Research
Centre
• RDM website:
http://www.ed.ac.uk/is/data-management
• RDM blog:
http://datablog.is.ed.ac.uk
• RDM wiki:
https://www.wiki.ed.ac.uk/display
/RDM/Research+Data+Management+
Wiki http://www.ed.ac.uk/is/data-management

TRAINING: MANTRA
 MANTRA is an internationally
recognized self-paced online
training course developed here
for PGR’s and early career
researchers in data
management issues.
 Anyone doing a research
project will benefit from at
least some part of the training –
discrete units
 Data handling exercises with
open datasets in 4 analytical
packages: R, SPSS, NVivo,
ArcGIS http://datalib.edina.ac.uk/mantra

TRAINING: TAILORED COURSES
 A range of training programmes
on research data management
(RDM) in the form of workshops,
power sessions, seminars and
drop in sessions to help
researchers with research data
management issues
 http://www.ed.ac.uk/schools-departments/
information-services/
research-support/data-management/
rdm-training
 Creating a data management plan
for your grant application
 Research Data Management
Programme at the University of
Edinburgh
 Good practice in Research Data
Management
 Handling data using SPSS
 Handling data with ArcGIS
http://edin.ac/1kRMPv3


PROGRESS SO FAR
Data Share – Live Now
DMPonline – Live Now
Website – Live Now
• Data Management Planning Support – Aug 2014
• Data Store – Roll-out completed by Dec 2014
• Training – Ongoing
• Awareness Raising - Ongoing
• Data Asset Register – Dec 2014
• Data Vault – Spring 2015

THANK YOU!
Acknowledgements:
Dr. Cuna Ekmekcioglu (Research & Learning Services)
Sarah Jones (Digital Curation Centre)
Stuart Lewis (Research & Learning Services)
Kerry Miller (Research & Learning Services)
Robin Rice (EDINA & Data Library)
Dr. Orlando Richards (IT Infrastructure)
Dr. John Scally (Library and Collections)
Tony Weir (IT Infrastructure)

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