Responsible Governance for a Food and Nutrition E-Infrastructure: Case Study of the Determinants and Intake Data Platform

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  • Lada Timotijevic
  • Indira Carr
  • Javier De La Cueva
  • Tome Eftimov
  • Charo E. Hodgkins
  • Barbara Koroušić Seljak
  • Mikkelsen, Bent Egberg
  • Trond Selnes
  • Pieter Van't Veer
  • Karin Zimmermann

The focus of the current paper is on a design of responsible governance of food consumer science e-infrastructure using the case study Determinants and Intake Data Platform (DI Data Platform). One of the key challenges for implementation of the DI Data Platform is how to develop responsible governance that observes the ethical and legal frameworks of big data research and innovation, whilst simultaneously capitalizing on huge opportunities offered by open science and the use of big data in food consumer science research. We address this challenge with a specific focus on four key governance considerations: data type and technology; data ownership and intellectual property; data privacy and security; and institutional arrangements for ethical governance. The paper concludes with a set of responsible research governance principles that can inform the implementation of DI Data Platform, and in particular: consider both individual and group privacy; monitor the power and control (e.g., between the scientist and the research participant) in the process of research; question the veracity of new knowledge based on big data analytics; understand the diverse interpretations of scientists' responsibility across different jurisdictions.

Original languageEnglish
Article number795802
JournalFrontiers in Nutrition
Number of pages14
Publication statusPublished - 23 Mar 2022

Bibliographical note

Funding Information:
The RICHFIELDS project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no. 654280 ( ).

Publisher Copyright:
Copyright © 2022 Timotijevic, Carr, De La Cueva, Eftimov, Hodgkins, Koroušić Seljak, Mikkelsen, Selnes, Van't Veer and Zimmermann.

    Research areas

  • big data, data quality, ethical, food consumer behavior, food consumer choice, interoperability, machine learning, standardization

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