Abstract

Bioscience has recently undergone a series of knowledge-based and technological revolutions. A critical consequence has been increasing recognition of the need to invest in infrastructure. Good access to data (and samples) from multiple studies is axiomatic to the value of this infrastructure. Access must be streamlined, secure, and based upon transparent and ‘fair’ decision making. It must be clear who has created and who has used which data. Ethico-legal policies and guidelines, which reflect dominant local cultural and societal norms, must take account of the increasingly global nature of bioscience research. A robust data infrastructure must also be attentive to the translational aims and social impact of its knowledge generation. In order to maintain the trust of its constituency – the general public as well as professional, political, commercial stakeholders – it must develop mechanisms to take account of all of these perspectives. These considerations form the basis of an emerging data economy. Building on extant achievements and pursuing the ideas outlined here could revolutionise the way we use and manage large-scale data. They have critical implications for biomedical and public health research communities and will be of central relevance for healthcare managers and policy makers, governments and industry. However, if the major challenges are to be met we must continue to invest,both nationally and internationally, in developing the cooperative infrastructures that provide a complementary foil to competitive resourcing mechanisms that drive hypothesis-driven science.

Highlights

  • Scientific advance involves the asking and answering of questions within constraints of contemporaneous knowledge and technology

  • The study of the etiological architecture of common chronic diseases demands that we explore much weaker effects [1,2] including interactions [3,4]

  • Solutions have been developed by these initiatives for some of the most pressing issues [7]: study cataloguing [18,21,26]; data harmonization [7,27]; and, ethico-legal, social and political issues underpinning data management and access [28,29]

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Summary

INTRODUCTION

Scientific advance involves the asking and answering of questions within constraints of contemporaneous knowledge and technology. Solutions have been developed by these initiatives for some of the most pressing issues [7]: study cataloguing [18,21,26]; data harmonization [7,27]; and, ethico-legal, social and political issues underpinning data management and access [28,29]. This paper highlights these solutions and additional endeavours that could dramatically change how we manage future data, in bioscience or -omics research but across domains using large-scale potentially shareable data (cf FlaReNet [30] and Gigascience [31])

Protecting participants
Identifying scientific contributions
ANALYSING DATA THAT CANNOT BE ACCESSED
MAINTAINING INTEGRITY
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