Speaker
Description
Open data is fundamental to open science, enhancing the trustworthiness and reproducibility of research alongside pre-registration. Many journals and European grants require data sharing and encourage compliance with the FAIR guidelines. However, despite its benefits, data sharing faces barriers, particularly around privacy.
GDPR mandates strict privacy protections that challenge the feasibility of anonymisation, especially in niche populations such as those in clinical or neurodivergent settings. Significantly, the AIP ethical code and, in multilab studies, the ethical standards of other nations, as well as the consent form, collectively play pivotal roles.
This talk will describe the inherent risks of data sharing, and present strategies to improve data anonymisation. It will explore potential solutions within the legal framework, acknowledging the complexities and ambiguities therein.
In addressing these challenges, we aim to strike a balance between the imperatives of open science and the rights of individuals to privacy and data protection.
| If you're submitting a symposium talk, what's the symposium title? | The Multiverse of Multi-labs. Methodological and Statistical Aspects of Multi-Lab and Multiverse Studies. |
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