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

Autor: Margaret D King, Dylan eWood, Brittny eMiller, Ross eKelly, William eCourtney, Drew eLandis, Runtang eWang, Jessica A Turner, Vince D Calhoun
Jazyk: angličtina
Rok vydání: 2014
Předmět:
Zdroj: Frontiers in Neuroinformatics, Vol 8 (2014)
Druh dokumentu: article
ISSN: 1662-5196
DOI: 10.3389/fninf.2014.00060
Popis: 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). Self Assessment (SAis an application embedded in the Assessment Manager tool in the 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. 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 the Mind Research Network behind a firewall to protect sensitive data. 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) are 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. There is a great need for data collection tools that limit human intervention and error. COINS aims to be a leader in database solutions for research studies collecting data from several different modalities
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