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 languageEnglish
Pages (from-to)1-6
Number of pages6
JournalarXiv
Publication statusPublished - 2 Dec 2018

Keywords

  • cs.CY
  • E.1; E.3; H.2.4; H.2.8

Cite this

@article{5fd44bdc772c45d6b5c1f9896972f462,
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.",
keywords = "cs.CY, E.1; E.3; H.2.4; H.2.8",
author = "Chang Sun and Lianne Ippel and Birgit Wouters and Soest, {Johan van} and Alexander Malic and Onaopepo Adekunle and Berg, {Bob van den} and Marco Puts and Ole Mussmann and Annemarie Koster and Kallen, {Carla van der} and David Townend and Andre Dekker and Michel Dumontier",
note = "6 pages, 1 figure, preliminary result, project report",
year = "2018",
month = "12",
day = "2",
language = "English",
pages = "1--6",
journal = "arXiv",
issn = "2331-8422",
publisher = "Cornell University",

}

Analyzing Partitioned FAIR Health Data Responsibly. / Sun, Chang; Ippel, Lianne; Wouters, Birgit; Soest, Johan van; Malic, Alexander; Adekunle, Onaopepo; Berg, Bob van den; Puts, Marco; Mussmann, Ole; Koster, Annemarie; Kallen, Carla van der; Townend, David; Dekker, Andre; Dumontier, Michel.

In: arXiv , 02.12.2018, p. 1-6.

Research output: Contribution to journalArticleAcademic

TY - JOUR

T1 - Analyzing Partitioned FAIR Health Data Responsibly

AU - Sun, Chang

AU - Ippel, Lianne

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

N1 - 6 pages, 1 figure, preliminary result, project report

PY - 2018/12/2

Y1 - 2018/12/2

N2 - 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.

AB - 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.

KW - cs.CY

KW - E.1; E.3; H.2.4; H.2.8

M3 - Article

SP - 1

EP - 6

JO - arXiv

JF - arXiv

SN - 2331-8422

ER -