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BD Hubs: Collaborative Proposal: WEST: Accelerating the Big Data Innovation Ecosystem

BD Hubs: Collaborative Proposal: WEST: Accelerating the Big Data Innovation Ecosystem
BD Hubs:协作提案:WEST:加速大数据创新生态系统
批准号:
1915774
负责人:
Edward Lazowska
金额:
$90.0万
依托单位:
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-06-01 至 2024-05-31

项目摘要

项目成果

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中文摘要
翻译
BD中心培育了区域利益相关者网络,并在美国对一个地区和国家至关重要的优先事项上在全国范围内进行合作。BD中心的活动为充满活力的国家数据创新生态系统做出了贡献。西部大数据创新中心建立和加强战略合作伙伴关系--利用数据革命来应对科学和社会挑战。无论是致力于数据知情医疗的未来,还是应对灾难恢复项目,该中心都设想了一个多元化的社区,有能力为国家优先领域做出贡献。这些中心专注于数据科学活动和倡议,这些活动和倡议激发了跨部门合作并例证了多学科方法的必要性。凭借这一奖项,西部大数据创新中心将:(1)在我们的主题领域开发和启用翻译数据科学(TDS)试点项目,以突出跨部门合作的价值,提高对现实世界用例的流畅性,并强调对数据和分析生命周期的务实和整体看法。我们预计2019-2023年我们的标志性TDS计划将包括:水与火:面向未来自然资源管理的数据协作;针对道路视频的压力测试访问;以及住房不稳定性:面向负责任数据管理的可信数据协作。(2)通过我们的活动促进不同利益相关者群体的团队组建,捕捉鼓舞人心的故事,并鼓励团队反思和分享他们对跨部门合作的见解。(3)提高对区域机遇的认识,并鼓励优先领域的工作,包括自然资源与危害、地铁数据科学、健康与医学、数据发现与学习、数据共享、云计算和负责任的数据科学。(4)支持数据科学教育和劳动力发展。认识到多元化、多方面的劳动力队伍是应对当前科学和社会挑战的关键,我们将继续扩大我们的教育和劳动力发展努力组合,包括专注于培训员培训课程、教学和实践、数据科学促进社会公益和数据科学团队、可查找的可访问的可互操作和可重复使用的(公平)数据以及制度变革--为扩大对数据科学的参与提供一个平台。我们在方案活动、社会技术共享资源和服务以及教育和劳动力发展活动方面取得进展的核心将是协调评估、将区域成功推广到国家大数据中心网络的机会,以及促进中心可持续性的战略努力,包括发展外部资金流。这些努力将旨在促进社区的参与并加强持续对话的渠道。这一奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The BD Hubs foster regional networks of stakeholders and cooperate nationally on US priorities of importance to a region and to the nation. The activities of the BD Hubs contribute to a vibrant national data innovation ecosystem. The West Big Data Innovation Hub builds and strengthens strategic partnerships -- harnessing the data revolution to address scientific and societal challenges. Whether working towards the future of data-informed healthcare or tackling projects in disaster recovery, the Hub envisions a diverse community empowered to contribute to areas of national priority. The Hubs focus on data science activities and initiatives that inspire cross-sector collaboration and exemplify the need for multi-disciplinary approaches.With this award, the West Big Data Innovation Hub will: (1) Develop and enable translational data science (TDS) pilot projects in our thematic areas to highlight the value of cross-sector collaboration, enhance fluency with real-world use cases, and emphasize a pragmatic and holistic view of the data and analytics lifecycles. We envision our signature TDS initiatives for 2019-2023 to include: Fire and Water: Data Collaborative for the Future of Natural Resource Management; Stress-Testing Access for Road Video; and Housing Instability: Trusted Data Collaborative for Responsible Data Management. (2) Facilitate team formation across different stakeholder groups through our activities, capturing inspirational stories and encouraging teams to reflect and share their insights about cross-sector collaboration. (3) Raise awareness of regional opportunities and inspire work in priority areas including Natural Resources & Hazards, Metro Data Science, Health & Medicine, Data-Enabled Discovery & Learning, Data Sharing, Cloud Computing, and Responsible Data Science. (4) Support data science education and workforce development. Recognizing that a diverse, multi-faceted workforce is key to addressing current scientific and societal challenges, we will continue to expand our portfolio of education and workforce development efforts, including a focus on Train-the-Trainer sessions, Pedagogy and Practice, Data Science for Social Good and the Data Science Corps, Findable Accessible Interoperable and Reusable (FAIR) data, and institutional change -- providing a platform for broadening participation in data science. Core to our progress in Programmatic Activities, Socio-Technical Shared Resources and Services, and Education and Workforce Development Activities will be a coordinated evaluation, opportunities for scaling regional successes to the national network of Big Data Hubs, and strategic efforts for Hub sustainability including the development of external funding streams. These efforts will be designed to enable community input and to strengthen channels for ongoing dialogue.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1145/3448016.3452777
发表时间: 2021-06
期刊: Proceedings of the 2021 International Conference on Management of Data
影响因子: --
作者: [An Yan;Bill Howe]
通讯作者: An Yan;Bill Howe
Identifying the Central Figure of a Scientific Paper
确定科学论文的中心人物
DOI: 10.1109/icdar.2019.00173
发表时间: 2019
期刊: 2019 International Conference on Document Analysis and Recognition (ICDAR
影响因子: --
作者: [Yang, Sean T., Lee, Po-Shen, Kazakova, Lia, Joshi, Abhishek, Oh, Bum Mook, West, Jevin D., Howe, Bill]
通讯作者: Howe, Bill
BD Hubs: Collaborative Proposal: WEST: A Big Data Innovation Hub for the Western United States
  • 批准号:
    1550224
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.18万
  • 财政年份:
    2015
  • 负责人:
    Edward Lazowska
  • 依托单位:
CC-NIE Network Infrastructure: Enhancements to Support Data-Driven Discovery at the University of Washington
  • 批准号:
    1244890
  • 项目类别:
    Standard Grant
  • 资助金额:
    $49.75万
  • 财政年份:
    2012
  • 负责人:
    Edward Lazowska
  • 依托单位:
Preparing Students and Teachers for Large-Scale Cluster Computing
  • 批准号:
    0836525
  • 项目类别:
    Standard Grant
  • 资助金额:
    $4.98万
  • 财政年份:
    2008
  • 负责人:
    Edward Lazowska
  • 依托单位:
The Computing Community Consortium
  • 批准号:
    0637190
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $0.0万
  • 财政年份:
    2006
  • 负责人:
    Edward Lazowska
  • 依托单位:
国内基金
海外基金
药物靶向β-catenin相分离调控肿瘤激 活型Loop Hubs抑制结直肠癌
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2025
  • 负责人:
    龚青
  • 依托单位:
超新星遗迹HUBS高分辨X射线观测的仿真模拟研究
  • 批准号:
    U1931140
  • 项目类别:
    联合基金项目
  • 资助金额:
    50.0万元
  • 批准年份:
    2019
  • 负责人:
    梁贵云
  • 依托单位: