Distributed Privacy-Preserving Data Analysis in NFDI4Health With the Personal Health Train
Keywords:Research Data Infrastructure, NFDI4Health, distributed data analytics, personal health train
Data sharing is often met with resistance in medicine and healthcare, due to the sensitive nature and heterogeneous characteristics of health data. The lack of standardization and semantics further exacerbate the problems of data fragments and data silos, which makes data analytics challenging. NFDI4Health aims to develop a data infrastructure for personalized medicine and health research and to make data generated in clinical trials, epidemiological, and public health studies FAIR (Findable, Accessible, Interoperable, and Reusable). Since this research data infrastructure is distributed over various partners contributing to their data, the Personal Health Train (PHT) complements this infrastructure by providing a required analytics infrastructure considering the distribution of data collections. Our research have demonstrated the capability of conducting data analysis on sensitive data in various formats distributed across multiple institutions and shown great potential to facilitate medical and health research.
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Copyright (c) 2023 Yongli Mou, Feifei Li, Sven Weber, Sabith Haneef, Hans Meine, Liliana Caldeira; Mehrshad Jaberansary; Sascha Welten, Yeliz Yediel Ucer, Guido Prause, Stefan Decker, Oya Beyan, Toralf Kirsten
This work is licensed under a Creative Commons Attribution 4.0 International License.
Grant numbers 442326535