Expediting the Production of High Value, Standardized, and Transparent Data

加快高价值、标准化、透明数据的产生

• 批准号: 8625842
• 负责人: P Allison Minugh
• 金额: $ 42.63万
• 依托单位: MJ DATA CORPORATION, LTD
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-15 至 2015-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8625842
• 关键词: Accountability; Address; Administrator; Affect; Algorithms; Archives; Automation; Businesses; Computer software; Computerized Patient Records; Contractor; Data; Data Analyses; Data Collection; Data Files; Data Quality; Data Reporting; Data Set; Databases; Decision Making; Development; Documentation; Education; Electronics; Ensure; Focus Groups; Generations; Government; Health; Housing; Marketing; Metadata; Mind; Modeling; Monitor; Occupations; Outcome; Phase; Practice Guidelines; Procedures; Process; Production; Publications; Publishing; Quality Control; Reporting; Research; Research Personnel; Science; Solutions; Sum; System; Technology; Testing; Time; Training; Universities; Walking; Work; cost effective; data management; data sharing; design; improved; innovation; pressure; prototype; research study; social; sound; syntax; tool; usability; user-friendly

DESCRIPTION (provided by applicant): Researchers and contractors are under increasing pressure to produce rapid turnaround times for data releases and publications. Inadequate data management is a common threat to good research and impedes the quick release of high value data. Despite its importance, many organizations do not have standardized data management practices that allow them to prepare high quality datasets quickly, effectively, and with transparency. As a result, production delays, inefficiencies, inconsistencies, and data errors are common. This proposal describes the development of a practical, user-friendly electronic tool, the Data ExpediterTM (DE) Syntax Generator, which uses step-by-step data management procedures combined with cutting edge, innovative algorithms to standardize and automate processes involved in creating high quality analytic files. Designed with researchers in health, social, and educational sciences in mind, the product walks the user through a best practice model for data management, specifically for tasks involved in creating clean and accurate data analytic files. Readily available metadata, syntax, and reports make monitoring studies, creating new databases, controlling data file releases, implementing changes, analyzing data, and training new project staff faster and more cost effective than ever. Phase I aims are to: (1) develop and test a working prototype; (2) conduct focus group research to assess the acceptance of the prototype; and (3) develop a full set of functional specifications. Upon demonstration of Phase I feasibility, Phase II aims are to: (1) build the commercialized DE Syntax Generator; (2) conduct usability testing to demonstrate ease of use; (3) conduct field tests in actual research settings at Harvard and Brown Universities; and (4) develop educational and product support materials. As an outcomes-driven innovation, the product will occupy a unique place in the market with its guided data management process and large array of automation tools. The products provides a unique and affordable solution to a common problem by using a standardized, uniform framework and automated syntax generation while allowing data users (e.g., researchers, administrators, those working with electronic patient records) to house data in their existing statistical software. The DE Syntax Generator replaces the chaotic, slow, and error-ridden, data management process with an organized, streamlined, and complete sequence of steps with interwoven quality control and automation to ensure rapid production of quality data. The DE Syntax Generator will improve the efficiency of studies, enhance data sharing, and decrease data and reporting errors. In sum, the product addresses an unmet need by helping researchers and data managers to follow state-of-the art practice guidelines for data management (transparency and proper documentation of all procedures) while getting the job done better, faster, and less expensively.

描述（由申请人提供）：研究人员和承包商面临着越来越大的压力，需要快速完成数据发布和出版物的周​​转时间。数据管理不足是良好研究的常见威胁，并阻碍高价值数据的快速发布。尽管它很重要，但许多组织没有标准化的数据管理实践，无法让他们快速、有效、透明地准备高质量的数据集。因此，生产延迟、效率低下、不一致和数据错误很常见。该提案描述了一种实用的、用户友好的电子工具的开发，即 Data ExpediterTM (DE) 语法生成器，它使用逐步的数据管理程序与尖端的创新算法相结合，以标准化和自动化创建高质量分析文件的流程。该产品专为健康、社会和教育科学领域的研究人员而设计，引导用户完成数据管理的最佳实践模型，特别是涉及创建干净、准确的数据分析文件的任务。随时可用的元数据、语法和报告使监控研究、创建新数据库、控制数据文件发布、实施变更、分析数据以及培训新项目人员比以往更快、更经济。第一阶段的目标是：（1）开发并测试工作原型； (2) 进行焦点小组研究，评估原型的接受度； (3)制定全套功能规范。在论证一期可行性后，二期目标是：（1）构建商业化的DE语法生成器； (2) 进行可用性测试以证明易用性； (3) 在哈佛大学和布朗大学的实际研究环境中进行现场测试； (4) 开发教育和产品支持材料。作为一种结果驱动的创新，该产品将凭借其引导数据管理流程和大量自动化工具在市场上占据独特的地位。该产品通过使用标准化、统一的框架和自动语法生成，为常见问题提供了独特且经济实惠的解决方案，同时允许数据用户（例如研究人员、管理员、处理电子病历的人员）将数据存储在现有的统计软件中。 DE 语法生成器用有组织、精简且完整的步骤序列取代了混乱、缓慢且充满错误的数据管理流程，并交织了质量控制和自动化，以确保快速生成高质量数据。 DE 语法生成器将提高研究效率、加强数据共享、减少数据和报告错误。总之，该产品通过帮助研究人员和数据管理人员遵循最先进的数据管理实践指南（所有程序的透明度和正确记录）来解决未满足的需求，同时更好、更快、更便宜地完成工作。