Analyzing Partitioned FAIR Health Data Responsibly

Chang Sun; Lianne Ippel; Birgit Wouters; Johan van Soest; Alexander Malic; Onaopepo Adekunle; Bob van den Berg; Marco Puts; Ole Mussmann; Annemarie Koster; Carla van der Kallen; David Townend; Andre Dekker; Michel Dumontier

Analyzing Partitioned FAIR Health Data Responsibly

Chang Sun, Lianne Ippel, Birgit Wouters, Johan van Soest, Alexander Malic, Onaopepo Adekunle, Bob van den Berg, Marco Puts, Ole Mussmann, Annemarie Koster, Carla van der Kallen, David Townend, Andre Dekker, Michel Dumontier

Research output: Working paper / Preprint › Preprint

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.

Original language	English
Publisher	Cornell University - arXiv
Pages	1-6
Number of pages	6
Publication status	Published - 2 Dec 2018

Publication series

Series	arXiv.org
ISSN	2331-8422

Keywords

cs.CY
E.1; E.3; H.2.4; H.2.8

Access to Document

https://arxiv.org/abs/1812.00991Licence: Unspecified

Cite this

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title = "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. ",

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AU - Sun, Chang

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AU - Wouters, Birgit

AU - Soest, Johan van

AU - Malic, Alexander

AU - Adekunle, Onaopepo

AU - Berg, Bob van den

AU - Puts, Marco

AU - Mussmann, Ole

AU - Koster, Annemarie

AU - Kallen, Carla van der

AU - Townend, David

AU - Dekker, Andre

AU - Dumontier, Michel

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