SESAM 2023 Workshop on "Open Access data sharing - How to make simulation-based training data Findable, Accessible, Interoperable and Reusable (FAIR)?"

Abstract

Open Access publishing is getting more and moreattention. Research is made available to the public and developing countries,giving more exposure. The underlying data, which can be qualitative (i.e.interview data) or quantitative (test scores, time to perform a task, simulatorparameters) are however often not shared. Publishing these data improvesreproducibility, accelerates innovation and allows for sharing of unique datanot available to everyone. We believe this is the next step forward inmaturation of the field of simulation applied to medicine and nursing. Thereare however perceived concerns regarding privacy and access under the EU generaldata protection regulation (GDPR). At the same time anonymization techniquesallow for data sharing and reuse under the GDPR.