课题基金 / 基金详情

NICHD DATA AND SPECIMEN HUB (DASH) MODERNIZATION

NICHD DATA AND SPECIMEN HUB (DASH) MODERNIZATION
NICHD 数据和样本中心 (DASH) 现代化
批准号:
10974899
负责人:
金额:
$380.9万
依托单位:
--
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-09-26 至 2024-09-25

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
Eunice Kennedy Shriver国家儿童健康和人类发展研究所(NICHD)建立了NICHD数据和标本中心(DASH),以促进NICHD资助研究的数据和生物标本的共享和访问。NICHD建立了DASH系统,以支持校外和校内研究部门(DER和ESTA),校内人口健康研究部门(DiPHR),国家医疗康复研究中心(NCMRR)和行政管理办公室(OAM)主任办公室的数据存储和数据及生物标本共享。DASH是一个Amazon Web Services云原生Web应用程序和数据存储库,托管并提供搜索界面,用于搜索近200项NICHD支持的研究、相关数据集和生物标本、这些研究的授权用户以及基于研究数据分析的出版物的链接信息。对于这些研究中的每一项,DASH系统安全地存储个体水平、去识别临床数据、研究元数据和研究文档文件。DASH Web应用程序为数据提交者、数据用户和NIH工作人员提供了直观的用户界面,并包含用于数据和生物样本访问请求的仪表板以及用于NIH工作人员的审查和报告仪表板。NICHD强烈鼓励研究所资助的所有研究人员在DASH数据存储库中共享来自人类的科学数据1,或使用DASH数据收集功能注册他们的研究及其数据和/或生物标本的位置。 NICHD 2020年战略计划在科学管理目标2,促进数据共享和获取生物标本中指出,“数据共享和获取生物标本有效地扩大了研究能力,并通过促进假设生成,增加二次分析的潜力和鼓励再现性来最大限度地提高NICHD的投资。NICHD将继续支持利用NICHD资金收集或创建的数据的实用性和可用性,并致力于保护人类参与者的隐私和机密性。 NICHD认为,当NIH资助的研究的科学数据和生物标本及时提供给更广泛的研究界时,研究投资的全部价值就可以实现。此外,所有NICHD内部和外部支持的研究人员将根据2023年1月生效的最终NIH数据管理和共享政策共享科学数据和研究资源,以进行更广泛的传播。NICHD数据科学和共享办公室正在领导DASH的现代化和扩展,以支持NICHD研究人员遵守NIH数据共享政策的能力,并确保共享的NICHD数据和生物标本可为更广泛的研究社区找到,访问,互操作和可重复使用。
英文摘要
The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) established the NICHD Data and Specimen Hub (DASH) to facilitate sharing of and access to data and biospecimens from NICHD-funded research. NICHD established the DASH system to support data storage and data and biospecimen sharing for the Divisions of Extramural and Intramural Research, (DER and DIR), Division of Intramural Population Health Research (DiPHR), National Center for Medical Rehabilitation Research (NCMRR), and the Office of the Director, Office of Administrative Management (OAM). DASH is an Amazon Web Services cloud-native web application and data repository that hosts and provides a search interface for linked information on nearly 200 NICHD-supported research studies, their associated datasets and biospecimens, authorized users of these studies, and the publications based on analysis of study data. For each of these studies, the DASH system securely stores individual level, deidentified clinical data, study metadata, and study documentation files. The DASH web application provides an intuitive user interface for data submitters, data users, and NIH staff and contains dashboards for data and biospecimen access requests and review and reporting dashboards for NIH staff. NICHD strongly encourages all investigators funded by the Institute to share scientific data1 derived from humans in the DASH data repository or to use the DASH Data Collections feature to register their studies and the location of their data and/or biospecimens. The NICHD Strategic Plan 2020 states in the Scientific Stewardship Goal 2, Facilitating Data Sharing and Access to Biospecimens, that “Data sharing and access to biospecimens efficiently expands research capacity and maximizes NICHD’s investments by promoting hypothesis generation, increasing the potential for secondary analyses, and encouraging reproducibility. NICHD will continue to support the utility and usability of data collected or created with NICHD funding, with a commitment to safeguarding human participants’ privacy and confidentiality,”https://www.nichd.nih.gov/about/org/strategicplan. NICHD believes that the full value of research investments can be realized when scientific data and biospecimens from NIH-funded research studies are made available in a timely manner to the broader research community. Further, all NICHD intramural and extramural-supported investigators will be expected to share scientific data and research resources for broader dissemination according to the Final NIH Policy for Data Management and Sharing, which goes into effect in January 2023. The NICHD Office of Data Science and Sharing is leading the modernization and expansion of DASH in order to support NICHD researchers’ ability to comply with NIH data sharing policies and to ensure that shared NICHD data and biospecimens are findable, accessible, interoperable, and reusable for the broader research community.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: