课题基金 / 基金详情

SCC: PuebloConnect: Expanding Internet Access and Content Relevance in Tribal Communities

SCC: PuebloConnect: Expanding Internet Access and Content Relevance in Tribal Communities
SCC:PuebloConnect:扩大部落社区的互联网访问和内容相关性
批准号:
1831698
负责人:
Elizabeth Belding
金额:
$200.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-10-01 至 2023-09-30

项目摘要

项目成果

Elizabeth Belding的其他基金

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中文摘要
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英文摘要
Our research addresses the dual goals of improving Internet access in economically marginalized communities while also building local capacity towards regular digital content creation. We focus on Native American reservation communities, which have among the lowest Internet availability rates in the nation. Our work will develop new network technologies to enable reservation residents to meaningfully participate in the Internet, as both consumers and producers of Internet content, in order to create new opportunities for economic development. To ensure the success of our technical work, we will engage community members in the planning, implementation, and dissemination of our research. Our team is partnered with non-profit, Native-serving, and community organizations that are actively working to solve digital inequities.To create a more usable Internet, we comprehensively rethink middle- and last-mile network technologies to offer adaptive, smart connectivity. Our fundamental contributions include: the disaggregation of control and data planes and a new content upload and download platform that bridges the gap between the network core and end system devices via a smart middle mile; Television (TV) spectrum white space pilot link deployments and network management solution and to study usability in rural regions; and collaboration with community partners through a participatory action research protocol to identify digital information needs and develop a framework for Web-design training to increase the Internet presence of Native-owned organizations. Because Native American reservations share many geographical and population density characteristics with other rural regions, many aspects of our work will be applicable to extending the reach and usability of the Internet to other, non-Native communities within the U.S.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(14)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1145/3446382.3448654
发表时间: 2021-02
期刊: Proceedings of the 22nd International Workshop on Mobile Computing Systems and Applications
影响因子: --
作者: [Esther H. Showalter;Morgan Vigil-Hayes;E. Zegura;R. Sutton;E. Belding-Royer]
通讯作者: Esther H. Showalter;Morgan Vigil-Hayes;E. Zegura;R. Sutton;E. Belding-Royer
Caring for Our People: Indigenous Responses to COVID-19 Era Informatic Colonialism
关爱我们的人民:土著对 COVID-19 时代信息殖民主义的反应
DOI: --
发表时间: 2021
期刊: Selected Papers of #AoIR2021 (SPIR
影响因子: --
作者: [Duarte, M, Deschine-Parkhurst, N., George, A., Soto, A.]
通讯作者: Soto, A.
Note: Towards Community-Empowered Network Data Action
注:迈向社区赋能的网络数据行动
DOI: 10.1145/3530190.3534836
发表时间: 2022
期刊: ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies (COMPASS
影响因子: --
作者: [Palacios Abad, Beatriz, Belding, Elizabeth, Vigil-Hayes, Morgan, Zegura, Ellen]
通讯作者: Zegura, Ellen
DOI: 10.1145/3579457
发表时间: 2023-04
期刊: Proceedings of the ACM on Human-Computer Interaction
影响因子: --
作者: [Beatriz Palacios Abad;Michael Koohang;Morgan Vigil-Hayes;E. Zegura]
通讯作者: Beatriz Palacios Abad;Michael Koohang;Morgan Vigil-Hayes;E. Zegura
11
    HSI Implementation and Evaluation Project: Integrated Networking, Scholarship, and Peer Mentoring of Freshmen Engineers for Increased Academic Success and Graduation Rates
    IMR: MM-1A: ADDRESS: Augment, Denoise and Debias cRowdsourced mEasurements for Statistical Synthesis of internet access characterization
    Collaborative Research: IMR: MM-1A: MapQ: Mapping Quality of Coverage in Mobile Broadband Networks using Latent Gaussian Process Models
    RAPID: Neighborhood-level U.S. Internet Accessibility Assessment through Dataset Aggregation and Statistical and Predictive Modeling