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Automated collection of imaging and phenotypic data to centralized and distributed data repositories

Accurate data collection at the ground level is vital to the integrity of neuroimaging research. Similarly important is the ability to connect and curate data in order to make it meaningful and sharable with other investigators. Collecting data, especially with several different modalities, can be t...

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Autores principales: King, Margaret D., Wood, Dylan, Miller, Brittny, Kelly, Ross, Landis, Drew, Courtney, William, Wang, Runtang, Turner, Jessica A., Calhoun, Vince D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4046572/
https://www.ncbi.nlm.nih.gov/pubmed/24926252
http://dx.doi.org/10.3389/fninf.2014.00060
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author King, Margaret D.
Wood, Dylan
Miller, Brittny
Kelly, Ross
Landis, Drew
Courtney, William
Wang, Runtang
Turner, Jessica A.
Calhoun, Vince D.
author_facet King, Margaret D.
Wood, Dylan
Miller, Brittny
Kelly, Ross
Landis, Drew
Courtney, William
Wang, Runtang
Turner, Jessica A.
Calhoun, Vince D.
author_sort King, Margaret D.
collection PubMed
description Accurate data collection at the ground level is vital to the integrity of neuroimaging research. Similarly important is the ability to connect and curate data in order to make it meaningful and sharable with other investigators. Collecting data, especially with several different modalities, can be time consuming and expensive. These issues have driven the development of automated collection of neuroimaging and clinical assessment data within COINS (Collaborative Informatics and Neuroimaging Suite). COINS is an end-to-end data management system. It provides a comprehensive platform for data collection, management, secure storage, and flexible data retrieval (Bockholt et al., 2010; Scott et al., 2011). It was initially developed for the investigators at the Mind Research Network (MRN), but is now available to neuroimaging institutions worldwide. Self Assessment (SA) is an application embedded in the Assessment Manager (ASMT) tool in COINS. It is an innovative tool that allows participants to fill out assessments via the web-based Participant Portal. It eliminates the need for paper collection and data entry by allowing participants to submit their assessments directly to COINS. Instruments (surveys) are created through ASMT and include many unique question types and associated SA features that can be implemented to help the flow of assessment administration. SA provides an instrument queuing system with an easy-to-use drag and drop interface for research staff to set up participants' queues. After a queue has been created for the participant, they can access the Participant Portal via the internet to fill out their assessments. This allows them the flexibility to participate from home, a library, on site, etc. The collected data is stored in a PostgresSQL database at MRN. This data is only accessible by users that have explicit permission to access the data through their COINS user accounts and access to MRN network. This allows for high volume data collection and with minimal user access to PHI (protected health information). An added benefit to using COINS is the ability to collect, store and share imaging data and assessment data with no interaction with outside tools or programs. All study data collected (imaging and assessment) is stored and exported with a participant's unique subject identifier so there is no need to keep extra spreadsheets or databases to link and keep track of the data. Data is easily exported from COINS via the Query Builder and study portal tools, which allow fine grained selection of data to be exported into comma separated value file format for easy import into statistical programs. There is a great need for data collection tools that limit human intervention and error while at the same time providing users with intuitive design. COINS aims to be a leader in database solutions for research studies collecting data from several different modalities.
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spelling pubmed-40465722014-06-12 Automated collection of imaging and phenotypic data to centralized and distributed data repositories King, Margaret D. Wood, Dylan Miller, Brittny Kelly, Ross Landis, Drew Courtney, William Wang, Runtang Turner, Jessica A. Calhoun, Vince D. Front Neuroinform Neuroscience Accurate data collection at the ground level is vital to the integrity of neuroimaging research. Similarly important is the ability to connect and curate data in order to make it meaningful and sharable with other investigators. Collecting data, especially with several different modalities, can be time consuming and expensive. These issues have driven the development of automated collection of neuroimaging and clinical assessment data within COINS (Collaborative Informatics and Neuroimaging Suite). COINS is an end-to-end data management system. It provides a comprehensive platform for data collection, management, secure storage, and flexible data retrieval (Bockholt et al., 2010; Scott et al., 2011). It was initially developed for the investigators at the Mind Research Network (MRN), but is now available to neuroimaging institutions worldwide. Self Assessment (SA) is an application embedded in the Assessment Manager (ASMT) tool in COINS. It is an innovative tool that allows participants to fill out assessments via the web-based Participant Portal. It eliminates the need for paper collection and data entry by allowing participants to submit their assessments directly to COINS. Instruments (surveys) are created through ASMT and include many unique question types and associated SA features that can be implemented to help the flow of assessment administration. SA provides an instrument queuing system with an easy-to-use drag and drop interface for research staff to set up participants' queues. After a queue has been created for the participant, they can access the Participant Portal via the internet to fill out their assessments. This allows them the flexibility to participate from home, a library, on site, etc. The collected data is stored in a PostgresSQL database at MRN. This data is only accessible by users that have explicit permission to access the data through their COINS user accounts and access to MRN network. This allows for high volume data collection and with minimal user access to PHI (protected health information). An added benefit to using COINS is the ability to collect, store and share imaging data and assessment data with no interaction with outside tools or programs. All study data collected (imaging and assessment) is stored and exported with a participant's unique subject identifier so there is no need to keep extra spreadsheets or databases to link and keep track of the data. Data is easily exported from COINS via the Query Builder and study portal tools, which allow fine grained selection of data to be exported into comma separated value file format for easy import into statistical programs. There is a great need for data collection tools that limit human intervention and error while at the same time providing users with intuitive design. COINS aims to be a leader in database solutions for research studies collecting data from several different modalities. Frontiers Media S.A. 2014-06-05 /pmc/articles/PMC4046572/ /pubmed/24926252 http://dx.doi.org/10.3389/fninf.2014.00060 Text en Copyright © 2014 King, Wood, Miller, Kelly, Landis, Courtney, Wang, Turner and Calhoun. http://creativecommons.org/licenses/by/3.0/ 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) or licensor 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
King, Margaret D.
Wood, Dylan
Miller, Brittny
Kelly, Ross
Landis, Drew
Courtney, William
Wang, Runtang
Turner, Jessica A.
Calhoun, Vince D.
Automated collection of imaging and phenotypic data to centralized and distributed data repositories
title Automated collection of imaging and phenotypic data to centralized and distributed data repositories
title_full Automated collection of imaging and phenotypic data to centralized and distributed data repositories
title_fullStr Automated collection of imaging and phenotypic data to centralized and distributed data repositories
title_full_unstemmed Automated collection of imaging and phenotypic data to centralized and distributed data repositories
title_short Automated collection of imaging and phenotypic data to centralized and distributed data repositories
title_sort automated collection of imaging and phenotypic data to centralized and distributed data repositories
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4046572/
https://www.ncbi.nlm.nih.gov/pubmed/24926252
http://dx.doi.org/10.3389/fninf.2014.00060
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