This is the authors' abstract. We don't add key points for this paper.
In this article, we examine work with communal data in the context of clinical genetic testing. Drawing from prior research on digital research infrastructures and from the analysis of our empirical data on genetic testing, we describe how data generated in laboratories distributed all over the world are shared and re-used. Our research findings point to six different human-driven activities related to expanding, disambiguating, sanitizing and assessing the relevance, validity and combinability of data. We contribute to research within Health Informatics with a framework that foregrounds human-driven activities for data interoperability.
Answers are grounded in this paper and cite their sources.
No takes yet. Share an insight, caveat, or question.
Vassilakopoulou et al. (2019) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: