1. Research Data Management (RDM): research ethics Research Ethics into the Digital Age, University of Sheffield. 11 April 2014 Laurian Williamson, Research Data Management Coordinator, University of Sheffield

2. 06/06/2016© The University of Sheffield Contents Research Data Management Research funders’ and institutional ‘data expectations’ Anonymisation and informed consent Data Management Plans (DMPs) A checklist Questions and discussion

3. What is research data? Definition depends on your subject discipline Research data refers to any type of data created, collected, or generated in a digital or non-digital form that is analysed to produce original research results. 06/06/2016© The University of Sheffield

4. What is research data management?

5. Research data lifecycle 06/06/2016© The University of Sheffield

6. Why manage research data? The data deluge –growth in volume of digital research data outputs (often created by publicly funded research) RDM expectations from research funders, publishers, and institutions Research data is increasingly viewed as a valuable research output 06/06/2016© The University of Sheffield

7. 06/06/2016© The University of Sheffield Why is managing research data important? Major drivers Research funder expectations, publishers, legislative frameworks, researchers as creators & users of data Good data management is good for research More efficient research process, avoids data loss, discoverability and increased reuse, preservation Good data management is good for UK HEIs Develop robust research infrastructure Research data is a valuable research output

8. Freedom of Information Act (FoIA) Freedom of information refers to a body of legislation that establishes the right of the public, or individual members of the public, to be given access to information from public bodies Although exemptions for research data exist, these may be subject to a ‘public interest test’ upon appeal 06/06/2016© The University of Sheffield

9. Research data and FoI requests There have been high profile cases involving research data from UK Universities Tobacco firm demands university's research on children and smoking "Stirling University fighting attempt by Philip Morris to gain access to research under freedom of information laws." September 2011. From: The GuardianThe Guardian University told to hand over tree ring data "Queen's University in Belfast has been told by the Information Commissioner to hand over 40 years of research data on tree rings, used for climate research." April 2010. From: BBC NewsBBC News University scientists in climategate row hid data "The university embroiled in the 'climategate' scandal refused to make its scientific data available to the public in breach of freedom of information laws, it has emerged." January 2010. From: The TelegraphThe Telegraph 06/06/2016© The University of Sheffield

10. Managing your data… Ensures the integrity of research and aids replication Ensures research data are accurate, complete, authentic and reliable Increases research efficiency Saves time, effort and resources in the long term Enhances data security and minimises the risk of data loss Prevents duplication of effort by enabling others to use your data Meet funders’ grant requirements Meet expectations of TUoS RDM Policy 06/06/2016© The University of Sheffield

11. 06/06/2016© The University of Sheffield Research data formats Text ‐ Flat text files, Word, Portable Document Format (PDF), Rich Text Format (RTF), Extensible Markup Language (XML). Numerical ‐ SPSS, Stata, Excel. Multimedia - jpeg, tiff, dicom, mpeg, quicktime. Models - 3D, statistical. Software - Java, C. Discipline specific - Flexible Image Transport System (FITS) in astronomy, Crystallographic Information File (CIF) in chemistry, Instrument specific - Olympus Confocal Microscope Data Format, Carl Zeiss Digital Microscopic Image Format (ZVI)

12. Research data types Documents (text, MS Word), spreadsheets Lab books, field notes, diaries Questionnaires, transcripts, codebooks Audiotapes, videotapes, photographs, images Slides, artefacts, specimens, samples Collection of digital objects acquired & generated during the research process Database contents (video, audio, text, images) Models, algorithms, scripts Contents of an application (input, output, logfiles for analysis software, schemas) Methodologies, workflows SOPs, protocols 06/06/2016© The University of Sheffield

13. Research Funders’ and their expectations

14. Research Funder expectations Timely release of data (‘exclusive use’ outlined in policies) Data to be discoverable, accessible, and where feasible, to be shared openly Long-term preservation of data (10yrs+) Data management plans (helps with research planning & navigating ethics and governance requirements) 06/06/2016© The University of Sheffield

15. RCUK Open Access Policy http://www.rcuk.ac.uk/documents/documents/RCUKOpenAccessPolicy.pdf From 01 st April 2013: “All papers must include details of the funding that supported the research and, if applicable, a statement on how the underlying research materials –such as data, samples or models –can be accessed.” 06/06/2016© The University of Sheffield

16. HORIZON 2020 Open Access to Research Data Data Management Plan a requirement What data will your project generate? How will it be exploited? Accessibility and verification Reuse Curation Long-term preservation 06/06/2016© The University of Sheffield

17. Funders’ RDM expectations 06/06/2016© The University of Sheffield

18. TUoS RDM Policy Approved by Senate in July 2012 Embedded within Good R&I Practices (GRIP) Policy http://www.shef.ac.uk/pol opoly_fs/1.356709!/file/G RIPPolicySenateapprove d.pdf Key expectation: “In the case of R&I activities involving human participants research data may need to be anonymised before release, in order to protect the identity of human participants.” 06/06/2016© The University of Sheffield

19. Research data may contain personal, confidential or sensitive data Personal data Personal data relate to an individual who can be identified from the data. Confidential data Confidential data are data given in confidence or data agreed to be kept confidential. Sensitive personal data Sensitive personal data are defined in the Data Protection Act 1998 as data on a person's race, ethnic origin, political opinion, religious or similar beliefs, trade union membership, physical or mental health or condition, sexual life, commission or alleged commission of an offence, proceedings for an offence (alleged to have been) committed, disposal of such proceedings or the sentence of any court in such proceedings. 06/06/2016© The University of Sheffield

20. Research data security Keep research data safe from corruption & control access Good research data security practice prevents: Accidental or malicious damage / modification to data Theft of valuable or irreplaceable data Breach of confidentiality agreements and privacy laws Release of data before it has been checked for accuracy and authenticity TuoS guidance http://www.sheffield.ac.uk/library/rdm/storagehttp://www.sheffield.ac.uk/library/rdm/storage 06/06/2016© The University of Sheffield

21. Informed consent Ethical requirement Gaining consent – make provision for sharing data Take into account immediate and future uses of data Failure to address informed consent may restrict data sharing opportunities 06/06/2016© The University of Sheffield

22. Research ethics and data sharing Some key principles: A duty of confidentiality towards informants and participants A duty to protect participants from harm, by not disclosing sensitive information Allow participants to make their own decisions on how the information they provide can be used, shared and made public (through informed consent) A duty to inform participants how information and data obtained will be used, processed, shared, disposed of, prior to obtaining consent A duty to wider society to make available resources produced by researchers with public funds (data sharing required by research funders) 06/06/2016© The University of Sheffield

23. Privacy and research data Individuals are normally considered to have a ‘right to privacy’ - the state of being free from intrusion or disturbance in one's private life or affairs Research proposals need to indicate how data will be collected about human subjects. Ethical reviews will consider how intrusive this is for the subjects The right to privacy implies the need to obtain consent from research subjects 06/06/2016© The University of Sheffield

24. Why anonymise data? Ethical reasons Protect people’s identity (sensitive and confidential) Disguise research location Legal reasons Do not disclose personal data (Data Protection Act) Commercial reasons 06/06/2016© The University of Sheffield

25. Remember to… Never disclose personal data (unless specific consent) Reasonable / appropriate level of anonymity Maintain maximum meaningful information Where possible replace rather than remove Re ‐ users of data have the same legal and ethical obligation to NOT disclose confidential information as primary users 06/06/2016© The University of Sheffield

26. Tips from the UK Data Archive Always consider anonymisation of research data together with consent agreements and access restrictions Regulating / restricting user access may offer a better solution than anonymising Avoid collecting data that requires anonymisation Remove, mask, change identifiers Retain unedited versions of data for use within the research team and for preservation Plan at start of research activity – not the end Freely available guidance and examples of anonymisation case studies available from: http://www.data-archive.ac.uk/create- manage/consent-ethics 06/06/2016© The University of Sheffield

27. Data Management Plans (DMPs)

28. What is a DMP? A short plan outlining: What data will be created How it will be ethically managed (stored, backed-up, accessed, encrypted) How the data will be shared and preserved DMPs are submitted as part of grant applications TUoS RDM Policy requirement that all research proposals for funded research must include a DMP 06/06/2016© The University of Sheffield

29. DMPs Make informed decisions to anticipate & avoid problems Avoid duplication, data loss and security breaches Develop procedures early on for consistency Ensure data are accurate, complete, reliable and secure Fulfil the funding requirements & the research objective 06/06/2016© The University of Sheffield

30. DCC Guidance and resources 06/06/2016© The University of Sheffield http://www.dcc.ac.uk/res ources/data- management-plans

31. Checklist  Have you consulted TUoS Research Ethics Policy?  Have you checked your funder’s policy on data sharing and deposit?  Have you obtained written consent for sharing and re-use from interviewees?  Have you spoken to CiCS about security and controlling access to personal/and or confidential information?  Have you stored information about the data’s sensitivity, participant consent or usage agreements alongside the material itself to avoid accidental misuse in future?  Have you informed interviewees and participants how:  Research material will be stored, preserved and used in the long- term?  Confidentiality will be maintained (by anonymising data)? 06/06/2016© The University of Sheffield

32. Thank you. Questions and comments l.williamson@sheffield.ac.uk or rdm@sheffield.ac.uk l.williamson@sheffield.ac.ukrdm@sheffield.ac.uk TUoS RDM website http://www.sheffield.ac.uk/library/rdm 06/06/2016© The University of Sheffield