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FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research
The effective sharing of health research data within the healthcare ecosystem can have tremendous impact on the advancement of disease understanding, prevention, treatment, and monitoring. By combining and reusing health research data, increasingly rich insights can be made about patients and popula...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233014/ https://www.ncbi.nlm.nih.gov/pubmed/37274750 http://dx.doi.org/10.3389/fninf.2023.1158378 |
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author | Behan, Brendan Jeanson, Francis Cheema, Heena Eng, Derek Khimji, Fatema Vaccarino, Anthony L. Gee, Tom Evans, Susan G. MacPhee, F. Chris Dong, Fan Shahnazari, Shahab Sparks, Alana Martens, Emily Lasalandra, Bianca Arnott, Stephen R. Strother, Stephen C. Javadi, Mojib Dharsee, Moyez Evans, Kenneth R. Nylen, Kirk Mikkelsen, Tom |
author_facet | Behan, Brendan Jeanson, Francis Cheema, Heena Eng, Derek Khimji, Fatema Vaccarino, Anthony L. Gee, Tom Evans, Susan G. MacPhee, F. Chris Dong, Fan Shahnazari, Shahab Sparks, Alana Martens, Emily Lasalandra, Bianca Arnott, Stephen R. Strother, Stephen C. Javadi, Mojib Dharsee, Moyez Evans, Kenneth R. Nylen, Kirk Mikkelsen, Tom |
author_sort | Behan, Brendan |
collection | PubMed |
description | The effective sharing of health research data within the healthcare ecosystem can have tremendous impact on the advancement of disease understanding, prevention, treatment, and monitoring. By combining and reusing health research data, increasingly rich insights can be made about patients and populations that feed back into the health system resulting in more effective best practices and better patient outcomes. To achieve the promise of a learning health system, data needs to meet the FAIR principles of findability, accessibility, interoperability, and reusability. Since the inception of the Brain-CODE platform and services in 2012, the Ontario Brain Institute (OBI) has pioneered data sharing activities aligned with FAIR principles in neuroscience. Here, we describe how Brain-CODE has operationalized data sharing according to the FAIR principles. Findable—Brain-CODE offers an interactive and itemized approach for requesters to generate data cuts of interest that align with their research questions. Accessible—Brain-CODE offers multiple data access mechanisms. These mechanisms—that distinguish between metadata access, data access within a secure computing environment on Brain-CODE and data access via export will be discussed. Interoperable—Standardization happens at the data capture level and the data release stage to allow integration with similar data elements. Reusable - Brain-CODE implements several quality assurances measures and controls to maximize data value for reusability. We will highlight the successes and challenges of a FAIR-focused neuroinformatics platform that facilitates the widespread collection and sharing of neuroscience research data for learning health systems. |
format | Online Article Text |
id | pubmed-10233014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102330142023-06-02 FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research Behan, Brendan Jeanson, Francis Cheema, Heena Eng, Derek Khimji, Fatema Vaccarino, Anthony L. Gee, Tom Evans, Susan G. MacPhee, F. Chris Dong, Fan Shahnazari, Shahab Sparks, Alana Martens, Emily Lasalandra, Bianca Arnott, Stephen R. Strother, Stephen C. Javadi, Mojib Dharsee, Moyez Evans, Kenneth R. Nylen, Kirk Mikkelsen, Tom Front Neuroinform Neuroscience The effective sharing of health research data within the healthcare ecosystem can have tremendous impact on the advancement of disease understanding, prevention, treatment, and monitoring. By combining and reusing health research data, increasingly rich insights can be made about patients and populations that feed back into the health system resulting in more effective best practices and better patient outcomes. To achieve the promise of a learning health system, data needs to meet the FAIR principles of findability, accessibility, interoperability, and reusability. Since the inception of the Brain-CODE platform and services in 2012, the Ontario Brain Institute (OBI) has pioneered data sharing activities aligned with FAIR principles in neuroscience. Here, we describe how Brain-CODE has operationalized data sharing according to the FAIR principles. Findable—Brain-CODE offers an interactive and itemized approach for requesters to generate data cuts of interest that align with their research questions. Accessible—Brain-CODE offers multiple data access mechanisms. These mechanisms—that distinguish between metadata access, data access within a secure computing environment on Brain-CODE and data access via export will be discussed. Interoperable—Standardization happens at the data capture level and the data release stage to allow integration with similar data elements. Reusable - Brain-CODE implements several quality assurances measures and controls to maximize data value for reusability. We will highlight the successes and challenges of a FAIR-focused neuroinformatics platform that facilitates the widespread collection and sharing of neuroscience research data for learning health systems. Frontiers Media S.A. 2023-05-18 /pmc/articles/PMC10233014/ /pubmed/37274750 http://dx.doi.org/10.3389/fninf.2023.1158378 Text en Copyright © 2023 Behan, Jeanson, Cheema, Eng, Khimji, Vaccarino, Gee, Evans, MacPhee, Dong, Shahnazari, Sparks, Martens, Lasalandra, Arnott, Strother, Javadi, Dharsee, Evans, Nylen and Mikkelsen. https://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 | Neuroscience Behan, Brendan Jeanson, Francis Cheema, Heena Eng, Derek Khimji, Fatema Vaccarino, Anthony L. Gee, Tom Evans, Susan G. MacPhee, F. Chris Dong, Fan Shahnazari, Shahab Sparks, Alana Martens, Emily Lasalandra, Bianca Arnott, Stephen R. Strother, Stephen C. Javadi, Mojib Dharsee, Moyez Evans, Kenneth R. Nylen, Kirk Mikkelsen, Tom FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research |
title | FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research |
title_full | FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research |
title_fullStr | FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research |
title_full_unstemmed | FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research |
title_short | FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research |
title_sort | fair in action: brain-code - a neuroscience data sharing platform to accelerate brain research |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233014/ https://www.ncbi.nlm.nih.gov/pubmed/37274750 http://dx.doi.org/10.3389/fninf.2023.1158378 |
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