1. Frameworks for Sensitive Data in the Research Lifecycle
John Southall Bodleian Data Librarian Subject Consultant for Economics, Sociology, Social Policy & Intervention Michaelmas 2016

2. Lifecycle Model Applicable throughout data lifecycle
Before a project
During a project
After completion
First two remain key
Third stage also now focus of policy and ‘expectations’
Management of sensitive and confidential data particularly affected by this
Various stakeholders and frameworks at work

3. Internal Frameworks Project Level University level
Define sensitivity – allows better management
Specific content or general content
Consent agreements with participants
Licensing agreements
University level
Policy requirements or ‘Expectations’
Applicable throughout data lifecycle

4. University Policy
Data should be retained for ‘as long as they are of continuing value to the researcher and the wider research community’ – but a minimum of three years
Researcher driven
Developing and documenting clear data management procedures
Planning for the ongoing custodianship of their data
Ensuring that legal, ethical, and funding body requirements are met
Institution responsible
for providing access to the services, facilities, and support needed to allow researchers to comply with the policy
Tagged as RDM

6. External frameworks Funder policy Collaborator policy and expectations
ESRC, EPSRC, Wellcome, RCUK Principles
Collaborator policy and expectations
Legal and Ethical policy
Data protection, FOI regulations
Privacy, confidentiality and consent
Broad consent arrangements need to accommodate all these

7. RCUK Guidance … on best practice in management of research data
Principle 4: RCUK recognises that there are legal, ethical and commercial constraints on release of research data. To ensure that the research process is not damaged by inappropriate release of data, research organisation policies and practices should ensure that these are considered at all stages in the research process.” (July 2015)

8. Discipline Based Guidance
Expectation = case by case discussion
MRC – produce DMP, deposit of appropriate data in ‘timely’ manner, with limited exclusivity clauses
EPSRC – produce DMP, preservation and sharing of data
ESRC – produce DMP,preservation of data wherever possible and deposit with institutional repository or UKDA or secure data lab
ESRC will dispute non-deposit proposals
All discussed as part of application process

10. Data Management Plan Place to consider the issues
Internal and external support for DMPs
Goal is to understand
Why your data is considered confidential or sensitive in some way
Impact of this on research process
How you manage it
where intent is that data/ sensitive data is not preserved or made accessible give a good reason
Staring point is to think about why your data is considered confidential or sensitive in some way.

11. Consent Agreements Help ensure participation Create trust
Define interests of stakeholders
Avoid agreements that are too restrictive
Or do not accommodate all three stages
“only to be used by this researcher” - “will be destroyed” - “no one else will read”
Helpful but not too restrictive
Protection for you - not a strait-jacket
Formal – defining - agreements

12. Three Approaches
Destruction
Alteration
Restriction

13. Destruction Dispose or destroy data when project ends Retention
Traditional solution in some disciplines
Wasteful?
Now requires good reason given
Will always be needed in some cases
Retention
Variant on destruction – rules out long term preservation
Oxford policy talks of minimum retention but does not mention maximum period
Does not imply destruction

14. Alteration Aggregation, anonymisation of data Fragmentation
Another traditional solution in some disciplines
Loss/ Degradation of content
Against expectations of data preservation?
Fragmentation
Helpful where specific content is the issue
Needs to be well defined and managed

15. Restriction
Anonymisation allows wide access to less data (ie by removing content)
An alternative approach is to leave content but make access harder
Relies on placing it somewhere with access control
E.g. Microdata from Eurostat
Vetting of access from UKDS
Requires clear access and usage conditions
Restrict what content may be reproduced
Introduce embargoes (last resort)

16. Conclusion Content is only starting point
Actual issue is how data will be used, managed, and disseminated.
Applicable throughout data lifecycle
Before a project – planned, approved or licenced
During – managed and secure
After – documented and preserved
Maintain confidentiality through controls on handling, storage and sharing
Use research design to reduce risks
Draw on RDM support at Oxford