The balance between openness and privacy for health data collected through citizen science: various perspectives

doi: 10.4121/20555505.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/20555505
Datacite citation style:
Ria Wolkorte; Michelle Kip; Lieke Heesink (2022): The balance between openness and privacy for health data collected through citizen science: various perspectives. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/20555505.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

Transcript of a 1.5 hour focus group discussion with 2 citizens, a data steward, an ethicist and a citizen science researcher. The group discussed their willingness to share data collected in citizen science for health projects in repositories, the desired level of openness, and how data sharing policies should be communicated with participants in the research projects. The discussion was held in Dutch, an English translation (translated by the reseachers themselves) is also available.

A public summary of the results can be found through this link:

https://www.topfitcitizenlab.nl/wp-content/uploads/2022/02/Outcomes-focusgroup-FAIR-and-privacy_english-1.pdf

The project was carried out as part of the TOPFIT Citizenlab, a fieldlab focusing on citizen science for health and wellbeing.

history
  • 2022-12-20 first online, published, posted
publisher
4TU.ResearchData
format
pdf
language
nl
funding
  • 4TU.ResearchData FAIR data fund spring 2021
organizations
University of Twente, Faculty of Behavioural, Management and Social Sciences (BMS), Health Technology & Services Research (HTSR);
University of Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Biomedical Signals and Systems (BSS)

DATA - restricted access

Reason

Choice of participants to keep data under embargo. Data contains personal, sensitive information

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