Analyzing Partitioned FAIR Health Data Responsibly
Abstract
It is widely anticipated that the use of health-related big data will enable further understanding and improvements in human health and wellbeing. Our current project, funded through the Dutch National Research Agenda, aims to explore the relationship between the development of diabetes and socio-economic factors such as lifestyle and health care utilization. The analysis involves combining data from the Maastricht Study (DMS), a prospective clinical study, and data collected by Statistics Netherlands (CBS) as part of its routine operations. However, a wide array of social, legal, technical, and scientific issues hinder the analysis. In this paper, we describe these challenges and our progress towards addressing them.
Keywords
Cite
@article{arxiv.1812.00991,
title = {Analyzing Partitioned FAIR Health Data Responsibly},
author = {Chang Sun and Lianne Ippel and Birgit Wouters and Johan van Soest and Alexander Malic and Onaopepo Adekunle and Bob van den Berg and Marco Puts and Ole Mussmann and Annemarie Koster and Carla van der Kallen and David Townend and Andre Dekker and Michel Dumontier},
journal= {arXiv preprint arXiv:1812.00991},
year = {2018}
}
Comments
6 pages, 1 figure, preliminary result, project report