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Big Data Needs Big Governance: Best Practices From Brain-CODE, the Ontario-Brain Institute’s Neuroinformatics Platform
The Ontario Brain Institute (OBI) has begun to catalyze scientific discovery in the field of neuroscience through its large-scale informatics platform, known as Brain-CODE. The platform supports the capture, storage, federation, sharing, and analysis of different data types across several brain diso...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6450217/ https://www.ncbi.nlm.nih.gov/pubmed/30984233 http://dx.doi.org/10.3389/fgene.2019.00191 |
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author | Lefaivre, Shannon Behan, Brendan Vaccarino, Anthony Evans, Kenneth Dharsee, Moyez Gee, Tom Dafnas, Costa Mikkelsen, Tom Theriault, Elizabeth |
author_facet | Lefaivre, Shannon Behan, Brendan Vaccarino, Anthony Evans, Kenneth Dharsee, Moyez Gee, Tom Dafnas, Costa Mikkelsen, Tom Theriault, Elizabeth |
author_sort | Lefaivre, Shannon |
collection | PubMed |
description | The Ontario Brain Institute (OBI) has begun to catalyze scientific discovery in the field of neuroscience through its large-scale informatics platform, known as Brain-CODE. The platform supports the capture, storage, federation, sharing, and analysis of different data types across several brain disorders. Underlying the platform is a robust and scalable data governance structure which allows for the flexibility to advance scientific understanding, while protecting the privacy of research participants. Recognizing the value of an open science approach to enabling discovery, the governance structure was designed not only to support collaborative research programs, but also to support open science by making all data open and accessible in the future. OBI’s rigorous approach to data sharing maintains the accessibility of research data for big discoveries without compromising privacy and security. Taking a Privacy by Design approach to both data sharing and development of the platform has allowed OBI to establish some best practices related to large-scale data sharing within Canada. The aim of this report is to highlight these best practices and develop a key open resource which may be referenced during the development of similar open science initiatives. |
format | Online Article Text |
id | pubmed-6450217 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-64502172019-04-12 Big Data Needs Big Governance: Best Practices From Brain-CODE, the Ontario-Brain Institute’s Neuroinformatics Platform Lefaivre, Shannon Behan, Brendan Vaccarino, Anthony Evans, Kenneth Dharsee, Moyez Gee, Tom Dafnas, Costa Mikkelsen, Tom Theriault, Elizabeth Front Genet Genetics The Ontario Brain Institute (OBI) has begun to catalyze scientific discovery in the field of neuroscience through its large-scale informatics platform, known as Brain-CODE. The platform supports the capture, storage, federation, sharing, and analysis of different data types across several brain disorders. Underlying the platform is a robust and scalable data governance structure which allows for the flexibility to advance scientific understanding, while protecting the privacy of research participants. Recognizing the value of an open science approach to enabling discovery, the governance structure was designed not only to support collaborative research programs, but also to support open science by making all data open and accessible in the future. OBI’s rigorous approach to data sharing maintains the accessibility of research data for big discoveries without compromising privacy and security. Taking a Privacy by Design approach to both data sharing and development of the platform has allowed OBI to establish some best practices related to large-scale data sharing within Canada. The aim of this report is to highlight these best practices and develop a key open resource which may be referenced during the development of similar open science initiatives. Frontiers Media S.A. 2019-03-29 /pmc/articles/PMC6450217/ /pubmed/30984233 http://dx.doi.org/10.3389/fgene.2019.00191 Text en Copyright © 2019 Lefaivre, Behan, Vaccarino, Evans, Dharsee, Gee, Dafnas, Mikkelsen and Theriault. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Lefaivre, Shannon Behan, Brendan Vaccarino, Anthony Evans, Kenneth Dharsee, Moyez Gee, Tom Dafnas, Costa Mikkelsen, Tom Theriault, Elizabeth Big Data Needs Big Governance: Best Practices From Brain-CODE, the Ontario-Brain Institute’s Neuroinformatics Platform |
title | Big Data Needs Big Governance: Best Practices From Brain-CODE, the Ontario-Brain Institute’s Neuroinformatics Platform |
title_full | Big Data Needs Big Governance: Best Practices From Brain-CODE, the Ontario-Brain Institute’s Neuroinformatics Platform |
title_fullStr | Big Data Needs Big Governance: Best Practices From Brain-CODE, the Ontario-Brain Institute’s Neuroinformatics Platform |
title_full_unstemmed | Big Data Needs Big Governance: Best Practices From Brain-CODE, the Ontario-Brain Institute’s Neuroinformatics Platform |
title_short | Big Data Needs Big Governance: Best Practices From Brain-CODE, the Ontario-Brain Institute’s Neuroinformatics Platform |
title_sort | big data needs big governance: best practices from brain-code, the ontario-brain institute’s neuroinformatics platform |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6450217/ https://www.ncbi.nlm.nih.gov/pubmed/30984233 http://dx.doi.org/10.3389/fgene.2019.00191 |
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