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COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets
The availability of well-characterized neuroimaging data with large numbers of subjects, especially for clinical populations, is critical to advancing our understanding of the healthy and diseased brain. Such data enables questions to be answered in a much more generalizable manner and also has the...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Research Foundation
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3250631/ https://www.ncbi.nlm.nih.gov/pubmed/22275896 http://dx.doi.org/10.3389/fninf.2011.00033 |
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author | Scott, Adam Courtney, Will Wood, Dylan de la Garza, Raul Lane, Susan King, Margaret Wang, Runtang Roberts, Jody Turner, Jessica A. Calhoun, Vince D. |
author_facet | Scott, Adam Courtney, Will Wood, Dylan de la Garza, Raul Lane, Susan King, Margaret Wang, Runtang Roberts, Jody Turner, Jessica A. Calhoun, Vince D. |
author_sort | Scott, Adam |
collection | PubMed |
description | The availability of well-characterized neuroimaging data with large numbers of subjects, especially for clinical populations, is critical to advancing our understanding of the healthy and diseased brain. Such data enables questions to be answered in a much more generalizable manner and also has the potential to yield solutions derived from novel methods that were conceived after the original studies’ implementation. Though there is currently growing interest in data sharing, the neuroimaging community has been struggling for years with how to best encourage sharing data across brain imaging studies. With the advent of studies that are much more consistent across sites (e.g., resting functional magnetic resonance imaging, diffusion tensor imaging, and structural imaging) the potential of pooling data across studies continues to gain momentum. At the mind research network, we have developed the collaborative informatics and neuroimaging suite (COINS; http://coins.mrn.org) to provide researchers with an information system based on an open-source model that includes web-based tools to manage studies, subjects, imaging, clinical data, and other assessments. The system currently hosts data from nine institutions, over 300 studies, over 14,000 subjects, and over 19,000 MRI, MEG, and EEG scan sessions in addition to more than 180,000 clinical assessments. In this paper we provide a description of COINS with comparison to a valuable and popular system known as XNAT. Although there are many similarities between COINS and other electronic data management systems, the differences that may concern researchers in the context of multi-site, multi-organizational data sharing environments with intuitive ease of use and PHI security are emphasized as important attributes. |
format | Online Article Text |
id | pubmed-3250631 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Frontiers Research Foundation |
record_format | MEDLINE/PubMed |
spelling | pubmed-32506312012-01-24 COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets Scott, Adam Courtney, Will Wood, Dylan de la Garza, Raul Lane, Susan King, Margaret Wang, Runtang Roberts, Jody Turner, Jessica A. Calhoun, Vince D. Front Neuroinform Neuroscience The availability of well-characterized neuroimaging data with large numbers of subjects, especially for clinical populations, is critical to advancing our understanding of the healthy and diseased brain. Such data enables questions to be answered in a much more generalizable manner and also has the potential to yield solutions derived from novel methods that were conceived after the original studies’ implementation. Though there is currently growing interest in data sharing, the neuroimaging community has been struggling for years with how to best encourage sharing data across brain imaging studies. With the advent of studies that are much more consistent across sites (e.g., resting functional magnetic resonance imaging, diffusion tensor imaging, and structural imaging) the potential of pooling data across studies continues to gain momentum. At the mind research network, we have developed the collaborative informatics and neuroimaging suite (COINS; http://coins.mrn.org) to provide researchers with an information system based on an open-source model that includes web-based tools to manage studies, subjects, imaging, clinical data, and other assessments. The system currently hosts data from nine institutions, over 300 studies, over 14,000 subjects, and over 19,000 MRI, MEG, and EEG scan sessions in addition to more than 180,000 clinical assessments. In this paper we provide a description of COINS with comparison to a valuable and popular system known as XNAT. Although there are many similarities between COINS and other electronic data management systems, the differences that may concern researchers in the context of multi-site, multi-organizational data sharing environments with intuitive ease of use and PHI security are emphasized as important attributes. Frontiers Research Foundation 2011-12-23 /pmc/articles/PMC3250631/ /pubmed/22275896 http://dx.doi.org/10.3389/fninf.2011.00033 Text en Copyright © 2011 Scott, Courtney, Wood, de la Garza, Lane, King, Wang, Roberts, Turner and Calhoun. http://www.frontiersin.org/licenseagreement This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited. |
spellingShingle | Neuroscience Scott, Adam Courtney, Will Wood, Dylan de la Garza, Raul Lane, Susan King, Margaret Wang, Runtang Roberts, Jody Turner, Jessica A. Calhoun, Vince D. COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets |
title | COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets |
title_full | COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets |
title_fullStr | COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets |
title_full_unstemmed | COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets |
title_short | COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets |
title_sort | coins: an innovative informatics and neuroimaging tool suite built for large heterogeneous datasets |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3250631/ https://www.ncbi.nlm.nih.gov/pubmed/22275896 http://dx.doi.org/10.3389/fninf.2011.00033 |
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