Research Data Management: Ethical Considerations
At a Glance
- If you are conducting any study involving human participants, and wish to make the data available at the end of the study then you need to consider from the very beginning when designing the study.
- In particular, informed consent must be given for a specific purpose, including future use of data and data sharing, if applicable to the research project.
- Anonymisation is a valuable tool that allows data to be shared, whilst preserving privacy. The process of anonymising data requires that identifiers are changed in some way such as being removed, substituted, distorted, generalised or aggregated.
Help@UCD: Office of Research Ethics
The Office of Research Ethics provides support and advice, including one-to-one consultations, for researchers going through the ethics review process.
Help@UCD: ISSDA - Anonymisation Workshop, June 22nd 2016
Social Media & Research
Administrative Data & Research
UCD Office of Research Ethics - Guidelines on the security and retention of research data
Responsibility for the management of research data
The Principal Investigator and/or researcher/supervisor is the custodian of the research data and is responsible for its management, including security, storage and retention. The Principal Investigator and/or researcher/supervisor is also responsible for informing the research participants of the researchers obligations in relation to the data.
Security of research data - access
The Principal Investigator and/or researcher/supervisor must determine and control access rights to research data. It is particularly important that access rights to personal data are strictly confined only to those who have been granted access . As well as ethical considerations , the privacy rights conferred by the Data Protection Acts 1988 and 2003 prohibit the processing of personal data without prior consent and, in the case of certain types of sensitive personal data, without the explicit written prior consent of the data subject. For the purpose of the Acts, processing includes storing, retrieving, accessing and retaining personal data. However personal data collected anonymously, or data that have been de-identified to the extent that the data subject can never again be identified from the data, do not come within the terms of the Acts.
Security of research data - storage
Once access rights have been established, data storage arrangements must also reflect the sensitivity of the data. Appropriate levels of storage security must therefore be established by the Principal Investigator and maintained by research participants. These will include strict protocols for the protection from unauthorised access of all physical and electronic locations where data are stored.
Retention of research data for duration of study
The Principal Investigator and/or researcher/supervisor must determine and make arrangements for the retention of data for appropriate periods following the conclusion of the project. Retention periods can vary depending on the research discipline, research purpose and type of data involved. They should therefore be determined on a project by project basis, taking into consideration any existing documented legal obligations governing retention periods, conditions imposed by research sponsors and the need to allow sufficient time for reference.
Once the period of retention has expired, research data must be disposed of or deleted securely and confidentially in a manner appropriate to its format.
Retention of research data for Archiving
The Principal Investigator and/or researcher/supervisor may wish to archive the collected data for the purposes of making it available for future use. You should consult with your school as they may have a policy on how they archive material.
The process of informed consent involves describing the research to potential participants. It is defined as “a process by which an individual voluntarily expresses his or her willingness to participate in a particular trial, after having being informed of all aspects of the study that are relevant to the decision to participate” (Harmonisation Guidelines for Good Clinical Practice (ICH GCP 1996)).
The researcher must explain to the participants the level of confidentiality of the research data and the measures that will be taken to ensure that confidentiality is maintained. In other words, they should provide a description of the steps that will be taken to protect the privacy of the participant and indicate under what circumstances records will be made available and to whom, including future use of data and data sharing, if applicable to the research project. Researchers should anticipate how the data may be used in the future and address it in the consenting procedure.
Personal data cannot be shared with a third party, unless specific and explicit consent is secured. Even if data is de-identified/anonymised prior to sharing it with a third party, this must be covered by valid consent of the person to whom the data pertains. Failure to properly address issues of consent may restrict the opportunities for initial use of data, the publishing of your results and the sharing of the data.
In order to make sure that research data can be made available for future reuse, it is important that consent for future reuse of the data by other researchers is sought from participants. Participants should be informed how research data will be stored, preserved and used in the long-term, and how confidentiality can be protected when needed.
Publishing and Sharing Sensitive Data
If you are conducting any study involving human participants, and wish to make the data available at the end of the study then you need to consider from the very beginning when designing the study. Enabling others to re-use your data will mean planning for this from the start of your research project. You will need to think critically of how research data can be shared, what might limit or prohibit data sharing (e.g. consent forms, confidentiality concerns), and whether any steps can be taken to remove such limitations. In paticular you will need to ensure you are asking for informed consent to share the data.
Key messages from ANDS Publishing and sharing sensitive data guide:
- The advantages of publishing your sensitive data will probably far outweigh any potential disadvantages when simple and appropriate steps are taken
- Publishing your data, or just a description of your data (that is the metadata), means that others can discover and cite it
- You can publish a description of your data without making the data itself openly accessible
- You can place conditions around access to published data
- Sensitive data that has been de-identified can be shared
Anonymisation is a valuable tool that allows data to be shared, whilst preserving privacy. The process of anonymising data requires that identifiers are changed in some way such as being removed, substituted, distorted, generalised or aggregated. Procedures to anonymise data should always be considered alongside obtaining informed consent for data sharing and imposing access restrictions.
It is not enough to simply remove direct identifiers from research data, it's also important to consider how indirect identifiers, or a combination of indirect identifiers, could lead to an individual being identified within the data.
A person's identity can be disclosed from:
- direct identifiers such as names, addresses, postcode information, telephone numbers or pictures
- indirect identifiers which, when linked with other publicly available information sources, could identify someone, e.g. information on workplace, occupation or exceptional values of characteristics like salary or age
Qualitative data anonymisation techniques:
- Remove major identifying data
- Remove all identifying details
- Replace with descriptions that reflect the significance of the original text within the context of the transcript
- Keep a tracking table to record all changes and to link real names with pseudonyms
- Indicate when a replacement has been made, e.g. @@Sarah##
Quantitative data anonymisation techniques:
- Remove direct identifiers
- names; addresses; telephone numbers; email addresses; photos; IP addresses
- Aggregate categories to reduce precision
- Band ages, incomes, expenditure etc. to disguise outliers
- Use standard coding frames, e.g. NUTS2
- Generalise meaning of detailed text
- Document the changes you make