The Mind Research Network Albuquerque, NM, USA.
The Mind Research Network Albuquerque, NM, USA ; Department of Psychology, Georgia State University Atlanta, GA, USA.
Front Neuroinform. 2014 Jun 5;8:60. doi: 10.3389/fninf.2014.00060. eCollection 2014.
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.
准确的实地数据收集对于神经影像学研究的完整性至关重要。同样重要的是能够连接和整理数据,以便使其具有意义并与其他研究人员共享。收集数据,特别是使用多种不同模式,可能既耗时又昂贵。这些问题推动了 COINS(协作信息学和神经影像学套件)中神经影像学和临床评估数据的自动化收集的发展。COINS 是一个端到端的数据管理系统。它为数据收集、管理、安全存储和灵活的数据检索提供了一个全面的平台(Bockholt 等人,2010 年;Scott 等人,2011 年)。它最初是为 Mind Research Network(MRN)的研究人员开发的,但现在已向全球神经影像学机构开放。自我评估(SA)是嵌入 COINS 中的评估管理器(ASMT)工具中的一个应用程序。它是一个创新的工具,允许参与者通过基于网络的参与者门户填写评估。它通过允许参与者直接将其评估提交给 COINS,从而消除了对纸质收集和数据输入的需求。仪器(调查)是通过 ASMT 创建的,包括许多独特的问题类型和相关的 SA 功能,可以实施这些功能来帮助评估管理的流程。SA 提供了一个仪器排队系统,具有易于使用的拖放界面,研究人员可以使用该界面为参与者设置队列。为参与者创建队列后,他们可以通过互联网访问参与者门户填写评估。这使他们能够灵活地从家中、图书馆、现场等地方参与。收集的数据存储在 MRN 的 PostgresSQL 数据库中。只有具有明确权限通过其 COINS 用户帐户访问数据并访问 MRN 网络的用户才能访问此数据。这允许进行大容量数据收集,并且用户对 PHI(受保护的健康信息)的访问最少。使用 COINS 的一个额外好处是能够收集、存储和共享成像数据和评估数据,而无需与外部工具或程序进行交互。收集的所有研究数据(成像和评估)都使用参与者的唯一主题标识符进行存储和导出,因此无需保留额外的电子表格或数据库来链接和跟踪数据。可以通过查询构建器和研究门户工具从 COINS 轻松导出数据,这些工具允许对数据进行细粒度选择,以便以逗号分隔值文件格式导出,以便轻松导入到统计程序中。需要数据收集工具来限制人为干预和错误,同时为用户提供直观的设计。COINS 的目标是成为一个数据库解决方案的领导者,用于从多种不同模式收集数据的研究。