Data privacy and GDPR
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Nicole McNeilly has developed an ethics approach based on the UK’s Economic and Social Research Council’s (ESCR) research ethics guidance. She draws out six main principles and gives information relating to this in each project:
Measures will be taken to ensure the quality and integrity of the research.
E.g. how quality and objectivity will be ensured.
E.g. how long data will be stored for.
Participants must give informed consent.
E.g. that participants are fully informed of the purpose, methods and intended possible uses of the research, before agreeing to share their data.
E.g. that data will not be shared with third parties.
The confidentiality and anonymity of research respondents will be respected.
E.g. how data will be collected, processed and reported on.
E.g. no quotes will be attributed to specific individuals, unless they give express permission for the researcher to do so, and they have the opportunity to say no with no repercussions.
E.g. how transcripts or notes from interviews or focus groups will be used or shared, why and how.
E.g. if data are collected anonymously, including, for example, measures taken (e.g. to ensure that IP addresses are not collected).
Participants will participate in the research voluntarily.
E.g. that all participation is voluntary and free from coercion.
E.g. that all participants have the right to refuse participation.
E.g. that participants can at any time request that their data are not used in the evaluation.
All measures will be taken to avoid harm to participants.
E.g. how you will minimise risks including physical and emotional harm and risk of upset, as well as reputational damage, for participants.
The research will be independent and impartial.
E.g. how conflicts of interest will be mitigated.
E.g. if respondents will be paid.
E.g. how the sample of those to be surveyed will be agreed.
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Impact webinar
You might be interested in our event (in collaboration with Europeana’s Diversity and Inclusivity Cross-Team) on diversity data collection. Explore what we discussed and the resources we collated to help you collect better data that helps you improve the diversity of your work. 🔽
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