The Data Cycle:
Managing & Sharing Data
Dr Tim Brooks and Julie Scott
Research, Development
& Commercial Services
Wednesday 13 June 2012
Session content
 What is data?
 Why make data publicly available?
 How to share your data
 Planning for preservation
 What Anglia Ruskin University is doing
What is data?
 Numerical, statistical, quantitative
 Interview transcripts & other qualitative data
 Video
 Audio
 Photographs & other (digital) images
Why make data publicly available
(for the research community)?
 Encourages scientific enquiry & debate
 Encourages innovation & new data users
 Leads to new collaborations between data users
& data creators
 Maximises transparency & accountability
 Increases the visibility of research
 Encourages the improvement & validation of
research methods
 Reduces the cost of duplicating research data
Why make data publicly available
(for you, the researcher)?
 Part of good research practice
 Funding body requirement (data management
plan) or journal publication requirement
 Codes of Practice
 Peer approval
 Citations
 Enhances value of research
 On-line accessibility
Why make data publicly available
(practical reasons)?
 Freedom of information requests
 Data not lost when researchers move on
 Data remains accessible over time
Reasons not to share data?
 Want to publish work before anyone sees the
data?
 Time/money & other practical constraints?
 Participants may not give consent?
 Audio-visual data – can’t be anonymised?
 Data not of interest to anyone else?
Risks?
 Breach of confidentiality to research participants
 Institutional/personal – exposure of data
 May be legal, ethical & commercial restraints
 Increased costs
 Version control
 Software updates & changes
 Data theft
Funders & data sharing
Funding bodies have different
expectations/requirements/approaches
Funding bodies which encourage data
sharing (1)
 Mandate researchers to offer research data
generated through research grants to
designated data centres (e.g. UK Data Archive &
NERC Data Centres)
 Economic & Social Research Council (ESRC)
 National Environment Research Council (NERC)
 British Academy
Funding bodies which encourage data
sharing (2)
 Encourage data sharing in timely manner –
Biotechnology & Biological Sciences Research Council
(BBSRC), Medical Research Council (MRC) & Wellcome
Trust
 Research programmes funded by multiple agencies
may mandate data sharing (e.g. cross-disciplinary Rural
Economy & Land Use Programme)
 Research councils fund data infrastructures & data
support services to facilitate data sharing within their
subject domain
Funding bodies which encourage data
sharing (3)
Economic & Social Research Council
(EPSRC)- 9 expectations & institutions
need to ensure compliance by May 2015
Most funders require data managing &
sharing plans for grant applications
How to share your data
 Send to a specialist data centre, data archive or
data bank
 Submit data to a journal in support of a paper
 Deposit in an Institutional repository
 Post to Project or institutional website
 Share directly with other researchers (Peer-topeer) basis
 Responsibility moving towards HEIs rather than
specialist centres
Advantages of depositing in specialist
data centre
 Quality standards
 Long-term preservation
 Data backed up regularly
 Licensing arrangements
 Standardised citation mechanism
 Monitoring secondary use of data
 Management of access to data & user queries
Examples of research data centres
UK Data Archive
History Data Service
UK Solar System Data Centre
National Biodiversity Network
Petrological Database of the Ocean Floor
Who does responsibility lie with?
 Researchers
 IT staff
 Support staff
 Institutions
 External collaborators
Planning for preservation (1)
 Ethics
- Consent
- Participant information sheet
- Anonymisation, if possible & desirable?
Planning for preservation (2)
Good research practice
Must plan throughout research lifecycle
Metadata
Types of documents stored e.g. photos
Can all be stored electronically?
Planning for preservation (3)
Quality assurance/data validation
Storage options
Version control
Document suites
Handling updates to data
Data curation (maintaining, preserving &
adding value to digital research data
throughout its lifecycle)
Common elements of data management
plan (DMP)
 Which data will be generated
 Metadata, standards & quality assurance
measures
 Plans for sharing data
 Ethical & legal issues or restrictions on data
sharing
 Copyright & intellectual property rights of data
 Data-storage & back-up measures
 Data management roles & responsibilities
 Costing or resourcing needed
DMP Online
 Digital Curation Centre (DCC) launched DMP
online in April 2010
 Web-based tool
 Researchers can create, store & update multiple
versions of a data management plan at the grant
application stage
 Can be customised
What Anglia Ruskin University is doing
Roadmap for Economic & Social Research
Council (EPSRC)
Service gap analysis
Business Plan
Training sessions
Institutional repository – ARRO
Background information
 http://www.dcc.ac.uk/ Digital Curation Centre [accessed
8 June 2012]
 http://www.epsrc.ac.uk/Pages/default.aspx EPSRC
[accessed 8 June 2012]
 http://www.rcuk.ac.uk/Pages/Home.aspx Research
Councils UK [Accessed 8 June 2012]
 University of Essex (2011) Managing & Sharing Data,
UK Data Archive, Best Practice for Researchers.
Any questions?