Managing Research Data –
The Organisational Challenge at Oxford
James A J [email protected]
Friday 6th December, 2013
The Growing Importance of Research Data Management
• Rise of data-driven research– Challenge to existing academic practices
– Opportunities for new kinds of research
• Increasing recognition of need to manage research data better– Opportunities for research communities
– Concern for reputations
– Mandates from research funders
Damaro Objectives
• Institutional RDM Policy
• Better understanding of researchers’ requirements
• Improved training & support materials – embedded in existing delivery
channels
• Design for connected RDM infrastructure, from planning to re-use
• ‘DataFinder’ software – to act as a catalogue of research data outputs
• Outputs that can be taken and adapted by other institutions
(project was part of the JISC MRD Programme)
• Sustainability
What is Research Data Management?
Planning
Literature / data review
Data analysis & research outputs
Data gathering
Documentation
Data deposit
Discovery
Long-term curation
Repository storage
File organisation & local storage
Idea
[Funding bid]
AccessRe-use
Principles behind Oxford’s infrastructure
• Modular
– Different business models for different components
– May be extended (or reduced)
• Researcher-focused
– Caters for different disciplines and working practices
• Intra-institutional
– Requires input from multiple support departments and
Academic Divisions
Demand
Demand for support with RDM from researchers
“My supervisor doesn’t want the whole dataset
to be made publicly available as it is. However,
he is very keen that whenever research papers
based on the data are published, relevant
portions of the data that support the findings are
also published.”
“Having a secure and fairly straightforward
means by which to share data with selected
collaborators around the world would be
extremely useful.”
“It would be useful for graduate students to learn
to pick the appropriate tool for the appropriate
question and the appropriate data … to know
what their options are.”
Essential -- My research would suffer significantly if my data were not properly managed
Important -- My research benefits from the time spent managing data
Helpful up to a point -- Time spent managing research data can make life easier further down the line, but it's not a very significant aspect of re-search
Not important -- Devoting time to managing research data would be a distraction from the real work of research
Importance of RDM
But fewer than a quarter had received any information about RDM from the University
Training Desired
1 Dealing with copyright, licensing, or other IP (intellectual property) issues relating to datasets 3.55
2 Preparing datasets for long-term preservation 3.42
3 Data documentation 3.34
4 Preparing datasets for sharing with researchers outside your research group 3.27
5 Storing data securely and backing up 3.13
6 Data management planning 3.13
7 Determining whether research datasets ought to be preserved after the end of a particular project 3.11
8 Organizing and structuring data within files (e.g. for analysis) 3.02
9 Version control 2.97
10 Managing bibliographic data 2.73
11 Organizing, structuring, and naming files and folders 2.66
Common RDM tasks ranked by mean level of desire for training :5 = most desired, 1 = least desired
Demand for support with RDM from above
“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.”
RCUK Common Principles on Data Policy
“data must be accessible and readily located; they must be intelligible to those
who wish to scrutinise them; data must be assessable so that judgments can
be made about their reliability and the competence of those who created them;
and they must be usable by others. For data to meet these requirements it
must be supported by explanatory metadata (data about data).”
Royal Society – Data as an Open Enterprise
Challenges
Diverse practices
• Principle of subsidiarity
• 45% of Departmental IT Managers reported that ‘every researcher /
research group is completely free to choose how they manage their
research data’
• 70% offer some departmental infrastructure to encourage a degree of
standard practice (e.g. shared drives, data deposit guidelines)
• 15% of departments have a departmental policy mandating particular
tools and processes that researchers should use for managing their data
• University RDM policy ratified in 2012, setting out responsibilities of
researchers and institution
Disciplinary requirements differ
• Significant differences in how researchers work
• Wide range of experience and confidence
amongst researchers
• Some disciplines already have good RDM
infrastructure in place, some keen for central
support– “The University should have a dedicated central
repository”
– “[The University should] develop a data
management service or be in a position to know
what to recommend to our researchers”
– “The desire to centralize … may work at the lower
end of the data requirements, but at the higher
end is rather naïve”
Humanities
Mathematical, Physical and Life Sciences
Medical Sciences
Social Sciences
0% 20% 40% 60% 80% 100%
As part of a team, with our research data managed by the team
As part of a team, but each member of the team looks after their own data
As an individual
Some of my re-search is under-taken as part of a team, but I also conduct some research inde-pendently
Researchers unclear where to go for support
IT Services
Departmental staff (including IT staff)
Academics & Colleagues
Research Services (including divisional & departmental)
National bodies (e.g. UKDA)
General web search
Libraries
OeRC
University website
Funders
RDM website
Other (suggestions with only 1 response)
Lack of staff confidence with RDM issues
Advise
on fi
le n
amin
g
Advise
on v
ersi
on contro
l
Assis
t in id
entif
ying IP
and o
ther
legal
issu
es
Help id
entif
y et
hical
& c
onfiden
tialit
y is
sues
Advise
on th
e fu
nder re
quirem
ents
for r
e-use
Advise
on w
ritin
g dat
a m
anag
emen
t pla
ns
Advise
on c
omplia
nce w
ithOxf
ord's
RDM p
olicy
Help id
entif
y th
e dat
a st
orage
require
men
ts
Raise
awar
enes
s of d
ata
secu
rity
issu
es
Advise
on h
ow to d
escr
ibe
the
data
within
pro
ject
Advise
on d
escr
ibin
g the
data
for f
uture
dis
cove
ry
Advise
on d
isse
min
atio
n optio
ns fo
r dat
a sh
arin
g
Advise
on is
sues
ass
ociat
ed w
ith li
censi
ng dat
a
Advise
on lo
ng-term
pre
serv
atio
n of d
ata
Advise
on th
e co
sts
asso
ciat
ed w
ith d
ata
cura
tion
Advise
on fu
nders'
require
men
ts fo
r re-
use o
f dat
a1
2
3
4
5
6
7
Not Confident
Completely Confident
Solutions
Who should support research data management?
Planning
Literature / data review
Data analysis & research outputs
Data gathering
Documentation
Data deposit
Discovery
Long-term curation
Repository storage
File organisation & local storage
Idea
[Funding bid]
Access and re-use
Research Services
IT Services
Library Services
Academic Divisions & Departments
Oxford eResearch Centre (OeRC)
COORDINATION
Role of Libraries
• Metadata
• Access
• Workflows
• Collection management
• Collection curation and preservation
• Service provision
• Systems
• But also contributions to training and good practice in earlier parts
of research life-cycle
Ongoing work
• Research services– OxfordDMPOnline & 20 questions for RDM
– Involvement of research facilitators
• IT Services– Implementing services for ‘live’ data (HFS, Servers and VMs, Supercomputing, ORDS)
– Research Support Group
• Libraries – DataBank
– DataFinder
– Involvement of Subject Librarians
• University coordination– Research Data Management and Open Data Working Group
Coordination
• Single point of contact
– Central RDM website
• Associated challenges
– Information / data / metadata flows
– RT systems
– Resourcing
– More organisational than technical
Questions?
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