Managing Research Data –

The Organisational Challenge at Oxford

James A J Wilsonjames.wilson@it.ox.ac.uk

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

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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?