When your research involves human participants (as opposed to math formulas or literature texts) there are more considerations that need to be taken into account, which are detailed below.
When dealing with human participants you may need to consult an ethics committee who will assess the ethical aspects of your research project before you start. This will especially be the case if you are dealing with more vulnerable participants (e.g., minors). Students rarely collect special categories of personal data (e.g., religious beliefs, sexual orientation), however if this is the case, consult your ethics committee. If you are in doubt, talk to your supervisor. A list of the ethics committees at Radboud University can be found here.
Personal data needs to be protected, safely stored and must not be shared publicly. [1]
Personal data are any information relating to an identified or identifiable living person. Personal data can be divided into two types:
Importantly, if a person’s identity is known or can be inferred, then any information you have about this person is considered personal data. Thus, if a person is identifiable, then this person’s gender is considered personal data as much as information you have about their favourite type of pizza.
Be particularly careful when collecting special categories of personal data, such as health data, political opinions, religious beliefs, someone’s sexual orientation etc. [2] These data can be used to discriminate against individuals and thus may only be collected when absolutely necessary and only when you have received approval from your local ethics committee and when you have obtained explicit consent from you participants.
[1]It is only possible to share personal data if the participants explicitly provided informed consent for this. This should only be done when absolutely necessary and should be approved by your local ethics committee.
If you have human participants you will most likely need to get informed consent.
More information on informed consent can be found here.
DO’S
DON’TS
For more information about privacy and security click here.
Whenever possible, de-identify data by anonymisation and if that is not possible (e.g., when running a longitudinal study) then by pseudonymisation.