Tânia Carvalho, Luís Antunes, Cristina Costa Santos, Nuno Moniz
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Empowering open data sharing for social good: a privacy-aware approach.
The Covid-19 pandemic has affected the world at multiple levels. Data sharing was pivotal for advancing research to understand the underlying causes and implement effective containment strategies. In response, many countries have facilitated access to daily cases to support research initiatives, fostering collaboration between organisations and making such data available to the public through open data platforms. Despite the several advantages of data sharing, one of the major concerns before releasing health data is its impact on individuals' privacy. Such a sharing process should adhere to state-of-the-art methods in Data Protection by Design and by Default. In this paper, we use a Covid-19 data set from Portugal's second-largest hospital to show how it is feasible to ensure data privacy while improving the quality and maintaining the utility of the data. Our goal is to demonstrate how knowledge exchange in multidisciplinary teams of healthcare practitioners, data privacy, and data science experts is crucial to co-developing strategies that ensure high utility in de-identified data.
期刊介绍:
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.