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ward.Instead of spending time and resources on complicated techniques to try to deidentify and anonymize complex patient data -and risk failing and making populations or patient groups skeptical about the whole concept of data sharing -it may be better to define a core set of data that can be released (and freely accessed) from all trials and to allow sharing of the more complex data only through real and inclusive collaborations, the way successful data sharing related to specific diseases already happens in global health today."It is not only about sharing of the raw data, but sharing of the questions, the problems, and the code that everybody is using," Shasha Jumbe said."It means collaborations throughout the whole process, definition of the goals, framing of the questions -and also thinking about inclusive attribution all the way from subjects that are part of these studies to the data science team.
Bierer et al. (Wed,) studied this question.
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