Supporting Research Data Management in Universities:

the Jisc Managing Research Data Programme

Simon Hodson

JISC Programme Manager, Managing Research Data

Wednesday 6 March 2013

KAPTUR Project Conference, RIBA, London

Why is managing research data important?

JISC considers it a priority to support universities in improving the way

research data is managed and, where appropriate, made available for reuse.

Research funder policies, legislative frameworks, good practice, open data

agenda

– The outputs of publicly funded research should be publicly available.

– The evidence underpinning research findings should be available for validation

Good data management is good for research

– More efficient research process, avoidance of data loss, benefits of data reuse

Alignment with university missions.

– Universities want to provide excellent research infrastructure.

– Universities want to have better oversight of research outputs.

What is Jisc doing?

Jisc Managing Research Data Programme: developing capacity and good

practice

– First MRD Programme, 2009-11: http://bit.ly/jiscmrd2009-11

– Selected outputs from the first programme: http://bit.ly/jiscmrd2009-11-outputs

– Second JISC MRD Programme, 2011-13: http://bit.ly/jiscmrd2011-13

– Programme Manager Blog: http://researchdata.jiscinvolve.org/

Digital Curation Centre: ‘because good research needs good data’

– Advice, guidance, advocacy, training in RDM: http://www.dcc.ac.uk/

– How to Guides: http://www.dcc.ac.uk/resources/how-guides

Janet Brokerage: Collaborative purchasing, B2B brokerage.

– Suite of services (generic research tools, cloud storage): https://www.ja.net/products-

services/janet-brokerage

STOP

What do we mean by research data?

STOP

What do we mean by research data?

The digital and other artifacts that are created

during the process of research, and which

through analysis form the evidence that underpins

research findings.

Data management and good research practice

Good data management is good practice

– Avoidance of data loss.

– Effective research: file naming, annotation etc: how do you find your data, how do

you understand it?

– ‘The first person with whom you share your data is your future self’!

Data sharing / data publication is good for research

– Verification of research findings / Deterrence of fraud

– Reproducibility of research / Science as a self-correcting process

– Benefits of data reuse: asking new questions of old data.

– Return on investment.

– Metastudies/systematic review: greater statistical value of integrated results.

– Integration of data in interdisciplinary research: the grand challenges require

multiple data sets

DUDs

The data centre under the desk (or in a back pack) is

not adequate.

Can we quantify the benefits

of reducing data loss?

Jisc Managing Research Data Programme project surveys have

uncovered evidence of data loss.

One survey found that 23.3% of respondents had lost research data

– 0.5 % had suffered catastrophic loss of all their research data as it had

not been backed up.

– 7.5 % had lost one week’s work

– 8 % had lost one day’s work

Royal Society

Science as an Open Enterprise Report, 2012

‘how the conduct and communication of

science needs to adapt to this new era

of information technology’.

‘As a first step towards this intelligent

openness, data that underpin a

journal article should be made

concurrently available in an

accessible database. We are now on

the brink of an achievable aim: for all

science literature to be online, for all of

the data to be online and for the two to

be interoperable.’

Royal Society June 2012, Science as an

Open Enterprise,

http://royalsociety.org/policy/projects/sci

ence-public-enterprise/report/

Science as an Open Enterprise Report:

six key changes

1. a shift away from a research culture where data is viewed as a private

preserve;

2. expanding the criteria used to evaluate research to give credit for useful

data communication and novel ways of collaborating;

3. the development of common standards for communicating data;

4. mandating intelligent openness for data relevant to published scientific

papers;

5. strengthening the cohort of data scientists needed to manage and support

the use of digital data (which will also be crucial to the success of private

sector data analysis and the government’s Open Data strategy);

6. the development and use of new software tools to automate and simplify the

creation and exploitation of datasets.

Royal Society 2012, Science as an Open Enterprise,

http://royalsociety.org/policy/projects/science-public-enterprise/report/

Drivers: Research Funder Policies

RCUK Common Principles on Data Policy: http://www.rcuk.ac.uk/research/Pages/DataPolicy.aspx

1. Public good: Publicly funded research data are produced in the public interest should be made openly available with as few restrictions as possible

2. Planning for preservation: Institutional and project specific data management policies and plans needed to ensure valued data remains usable

3. Discovery: Metadata should be available and discoverable; Published results should indicate how to access supporting data

4. Confidentiality: Research organisation policies and practices to ensure legal, ethical and commercial constraints assessed; research process should not be damaged by inappropriate release

5. First use: Provision for a period of exclusive use, to enable research teams to publish results

6. Recognition: Data users should acknowledge data sources and terms & conditions of access

7. Public funding: Use of public funds for RDM infrastructure is appropriate and must be efficient and cost-effective.

DCC Overview of Funder Data Policies: http://www.dcc.ac.uk/resources/policy-and-legal/overview-funders-data-policies

EPSRC Research Data Policy Expectations

Policy and expectations:

http://www.epsrc.ac.uk/about/standards/researchdata/Pages/policyframework.aspx

Research organisations to have RDM policy, advocacy and support functions. (i, iii)

Research data to be effectively managed and curated throughout the life-cycle (viii)

Research organisations to maintain public catalogue of research data holdings,

adequate metadata and permanent identifier (v)

Publications to indicate how research data can be accessed (ii)

Data to be retained for 10 years from last access (vii)

Research data management to be adequately resourced from appropriate funding streams

(ix)

Roadmap in place by 1 May 2012

Compliance by 1 May 2015

Barriers to data sharing…

Researchers concerns:

– Concern that data may be misused or misunderstood.

– Concern that will lose scientific edge if sharing before fully exploited.

– Desire to retain control of a professional asset.

– Concern that will not be credited.

– Lack of career rewards for data publication.

See ODE report, using Parse.Insight findings: http://www.alliancepermanentaccess.org/wp-

content/uploads/downloads/2011/11/ODE-ReportOnIntegrationOfDataAndPublications-1_1.pdf

RIN Report, ‘To Share or not to share’, http://www.rin.ac.uk/our-work/data-management-and-curation/share-or-not-

share-research-data-outputs

Professional benefits of data sharing

“authors who make data from their articles available are cited twice

as frequently as articles with “no data but otherwise equivalent

credentials, including degree of formalization.”” -- Glenditsch, Petter,

Metelits, and Strand (2003: 92)

“48% of trials with

publicly available

microarray data

received 85% of the

aggregate citations”

-- Piwowar HA, Day RS,

Fridsma DB (2007) Sharing

Detailed Research Data Is

Associated with Increased

Citation Rate. PLoS ONE

2(3): e308.

“We find strong and consistent evidence that

data sharing, both formal and informal,

increases research productivity across a wide

range of publication metrics. Data archiving,

in particular, yields the greatest returns on

investment with research productivity

(number of publications) being greater when

data are archived. Not sharing data, either

formally or informally, limits severely the

number of publications tied to research data.” –

Pienta, Alter, Lyle (2010) The Enduring Value of

Science Research: The Use and Reuse of Primary

Research Data.

Slide credit, Joss Winn, University of Lincoln

Research data are an asset! Imagine the significance of the research collections of key departments/research groups, departed alumni. Don’t underestimate the research value of the stuff that underpins your research, that you make during your research.

Building Institutional Capacity:

Second MRD Programme, 2011-13

Second JISC MRD Programme, 2011-13: http://bit.ly/jiscmrd2011-13

Institutional RDM

Infrastructure Services

17 Projects

RDM Training

5 projects

RDM Planning

10 projects

Data Publication

3 projects

Ownership: High level

ownership of the problem,

senior manager on

steering .

Sustainability: Large

institutional contributions.

Develop business cases

to sustain work.

Encouraged to reuse

outputs from first

programme and

elsewhere.

Mix of pilot projects and

embedding projects.

Holistic institutional

approach to RDM.

Jisc MRD RDM Infrastructure Projects

Data Management Planning

Managing Active Data

Processes for selection and

retention Deposit / Handover

Data Repositories/Catalogu

es

Components of research data management support services

RDM Policy and Roadmap Business Plan and

Sustainability

Guidance, Training and Support

Research Data Registry

Data Management Planning

Selection and Retention Deposit / Handover

Advocacy, Guidance, Training and Support

RDM Policy and Roadmap

Business Plan and Sustainability

DMPonline

Guidance

Templates

DataStage

Academic Dropbox

Active Storage

Guidance

Good Practice

Case Studies

SWORD Protocol

Easy Uploader

Metadata Identifiers Guidance

Coordination

Jisc / Jisc-mediated Products

Guidance

Good Practice

Coordination

Research Data Registry

Training and Advocacy Resources

Institutional RDM Support Service Jisc / Jisc-mediated

Products

Archival Storage

Data Repositories/Catalo

gues

Managing Active Data

Products map to components of RDM support services. Arrows in indicate products delivered. Red arrows out indicates data hosting or metadata transfer to external service.

University RDM Guidance Pages

http://www.gla.ac.uk/services/datamanagement/

University RDM Guidance Pages

http://www.admin.ox.ac.uk/rdm/

University RDM Guidance Pages

http://www.bath.ac.uk/research/data

University RDM Guidance Pages

http://www.southampton.ac.uk/library/research/researchdata/

University RDM Guidance Pages

http://www2.le.ac.uk/services/research-data

Institutional Policies and Roadmaps

Institutional Research Data Management Policies:

http://www.dcc.ac.uk/resources/policy-and-legal/institutional-data-policies/uk-

institutional-data-policies

Institutional Roadmaps to meet EPSRC Expectations on Research Data:

http://www.dcc.ac.uk/resources/policy-and-legal/epsrc-institutional-roadmaps

Data Management Planning

Jez Cope, University of Bath, R360 Project http://opus.bath.ac.uk/30772/

Detailed guidance on funder requirements for DMPs from DCC:

http://www.dcc.ac.uk/sites/default/files/documents/resource/policy/FundersData

PlanReqs_v4%204.pdf

DCC How to Develop a Data Management and Sharing Plan:

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

DCC DMPonline tool: https://dmponline.dcc.ac.uk/

JISCMRD Training Projects Phase 1 and 2

Need for subject focussed research data management / curation training, integrated with

PG studies

Five projects in the first programme to design and pilot (reusable) discipline-focussed

training units for postgraduate courses:

http://www.jisc.ac.uk/whatwedo/programmes/mrd/rdmtrain.aspx

Heath studies; creative arts; archaeology and social anthropology; psychological sciences;

social sciences and geographical sciences: http://www.dcc.ac.uk/training/train-

trainer/disciplinary-rdm-training/disciplinary-rdm-training

Four projects in the second programme:

http://researchdata.jiscinvolve.org/wp/2012/08/23/research-data-management-training-five-

new-jiscmrd-projects/

Psychology and computer science; digital music; physics and astronomy; subject and

liaison librarians.

MANTRA Training Materials, University of Edinburgh

Online course built using OS Xerte

toolkit.

Sections include:

– DMPs

– Organising Data

– File Formats and Transformation

– Documentation and Metadata

– Storage and Security

– Data Protection

– Preservation, sharing and licensing

Also software practicals for users of

SPSS, R, ArcGIS, Nvivo

Research Data MANTRA:

http://datalib.edina.ac.uk/mantra/

Lincoln Orbital Project: Joining up Institutional Systems: http://orbital.blogs.lincoln.ac.uk/2012/12/06/orbital-deposit-of-dataset-records-to-the-lincoln-

repository-workflow/

University Data Repositories

https://ore.exeter.ac.uk/repository/handle/10871/502

University Data Repositories

http://data.bris.ac.uk/datasets/12mjtnrtsdjfs17sl4pq2ucqrk/

University Data Repositories

https://databank.ouls.ox.ac.uk/general/datasets/Tick1AudioCorpus

Metadata Schema for Institutional Data Repositories

http://www.data-archive.ac.uk/media/375386/rde_eprints_metadataprofile.pdf

Development of Institutional RDM Capacity

The Royal Society Science as an Open Enterprise report recommended that

the JISC Managing Research Data Programme ‘should be expanded beyond

the pilot 17 institutions within the next five years.’

[Royal Society 2012, Science as an Open Enterprise, p.73]

You and research data/research outputs… 1. Does your institution have an

RDM policy and a set of guidance pages supporting it?

2. Does your institution provide support for data management during your research?

3. Does your institution have a repository for research data?

4. Do you know how to prepare a data management plan?

5. Which data do you retain at the end of a research project?

6. Would you reference data in your published research?

7. Which data would you retain at the end of a project and how would you make this available?

Thank You

JISC Managing Research Data Programme: http://bit.ly/jiscmrd2009-11

JISC MRD Programme Blog: http://researchdata.jiscinvolve.org/wp/

Jisc MRD Programme List: https://www.jiscmail.ac.uk/cgi-

bin/webadmin?A0=JISCMRD

RESEARCH-DATAMAN Discussion List: https://www.jiscmail.ac.uk/cgi-

bin/webadmin?A0=RESEARCH-DATAMAN

E-mail: s.hodson@jisc.ac.uk

Twitter: @simonhodson99 ; #jiscmrd