权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Spokes: MEDIUM: MIDWEST: Collaborative: Community-Driven Data Engineering for Substance Abuse Prevention in the Rural Midwest

辐条：媒介：中西部：协作：社区驱动的数据工程，用于中西部农村地区的药物滥用预防

基本信息

批准号：
1761969
负责人：
Raghu Machiraju
金额：
$ 65.1万
依托单位：
Ohio State University
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
起止时间：
2018-09-01 至 2022-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1761969&HistoricalAwards=false
关键词：
Spokes MEDIUM MIDWEST Collaborative Community

项目摘要

The opioid crisis ravaging Ohio and the Midwest disproportionally affects small and rural communities. Harnessing and deploying data holds promise for developing a response to this crisis by policymakers, healthcare providers, and citizens of the communities. Currently, there are many barriers to getting data into the hands of individuals on the frontlines. Crucial data are siloed across law enforcement, public health departments, hospitals and clinics, and county administrations; data often are inaccurate or collected in non-standard ways across different agencies and departments; the stigma of drug abuse limits accurate reporting of drug-related deaths; and information is not shared with the community and other stakeholders because of the lack of a privacy and security framework. Such barriers, for example, prevent individuals with addictions or their families and friends from locating available treatment centers or obtaining other important information in a timely way. Similarly, it is difficult for first responders and healthcare providers to obtain critical up-to-date information. In predominantly rural counties, these challenges are especially daunting because there is often poor connectivity and communication infrastructure. This Big Data Spoke project involves developing scalable, flexible, and connectivity-rich data-driven approaches to address the opioid epidemic. The cyberinfrastructure framework, OpenOD, will be initially designed and deployed in small and rural communities in Appalachia Ohio and the Midwest, where the need for data and connection are greatest. Based upon significant community input, OpenOD will also create end-user applications or enterprise solutions to support stakeholders and communities to mount a response they feel will be most efficient and beneficial at the local level. As a Spoke to NSF?s Midwest Big Data Hub, our efforts can be efficiently scaled, disseminated, and applied to the opioid and other societal problems such as infant mortality, crime, and natural disasters. This project fits within NSF's mission to promote the progress of science (contribute to the science and engineering of large socially relevant cyberinfrastructures) to advance the health and welfare of US citizens (by linking data sources in new and useful ways to empower communities to address societal problems; establishing sustainable partnerships between academia, industry, government and communities; increasing data literacy and community engagement with data science; and enhancing research and education via development/adaptation of training modules and courses in data analytics).The main goal of this project is to help small and rural communities in the Midwest address the opioid epidemic via BIGDATA (BD) technology. While no communities have been spared, small and rural communities face unique challenges in confronting the opioid epidemic: knowledge and data exist in siloes across multiple organizations with varying jurisdictional boundaries; efforts to collect, link, and analyze data are hampered by a lack of infrastructure and tools; rural areas are plagued by "dead zones" in cellular connectivity; communities lack capacity for data collection, and analytics; needs and resources across effected communities are not uniform and require BD approaches that are flexible, open, leverage significant community input, and can be dutifully validated. Our proposed solution is OpenOD, a framework that provides uniform, relevant and timely access to data. Working integrally with the Midwest Big Data Hub (MBDH) and our partners, our three main objectives are to: (1) Work with local communities to understand strengths and gaps in cyberinfrastructure, data availability, and need for data analytics workforce skills. (2) Assemble flexible cyberinfrastructure that includes a data commons, stakeholder-usable and cloud-amenable data analytics and visualization tools, and internet connectivity with both mobile and non-mobile capabilities. (3) Validate, evaluate, and disseminate cyberinfrastructure and data analytics tools to stakeholder groups throughout the region while fostering new partnerships. OpenOD will create approaches that will allow governing units to deploy openly available tools rather than rely on proprietary tools. In this way, existing disparities in data access and ensuing responses are effectively addressed. The potential contributions of the project are to: (1) Increase BD and STEM literacy and community engagement in underrepresented groups given the operating milieu of OpenOD in rural areas where the population is indigent and lacks adequate skills to join the modern workforce. (2) Improve well-being of individuals in society by linking data sources in new and useful ways to empower communities to address the opioid crisis; improved connectivity and timely delivery of critical information will accelerate community responsiveness and improve preventive strategies. (3) Provide infrastructure for research and education will be improved given that project activities will deliver linked, curated data sets to community stakeholders, researchers and educators. Training modules and courses adapted and developed and shared with local/regional educators and will remain with the communities after the funding period has ended. In addition, new and established partnerships will allow sustainability of the project in the communities for the long-term.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.

肆虐俄亥俄州和中西部的阿片类药物危机严重影响了小型和农村社区。利用和部署数据有望为决策者、医疗服务提供者和社区公民制定应对这场危机的措施。目前，将数据送到前线个人手中存在许多障碍。关键数据在执法部门、公共卫生部门、医院和诊所以及县行政部门之间被孤立;数据往往不准确，或在不同机构和部门以非标准方式收集;药物滥用的耻辱限制了对与药物有关的死亡的准确报告;由于缺乏隐私和安全框架，信息没有与社区和其他利益攸关方共享。例如，这些障碍阻止成瘾者或他们的家人和朋友找到可用的治疗中心或及时获得其他重要信息。同样，急救人员和医疗保健提供者也很难获得关键的最新信息。在以农村为主的县，这些挑战尤其艰巨，因为那里的连通性和通信基础设施往往很差。这个大数据辐条项目涉及开发可扩展的，灵活的和连接丰富的数据驱动的方法来解决阿片类药物的流行。网络基础设施框架OpenOD最初将在阿巴拉契亚俄亥俄州和中西部的小型和农村社区设计和部署，那里对数据和连接的需求最大。基于大量的社区投入，OpenOD还将创建最终用户应用程序或企业解决方案，以支持利益相关者和社区做出他们认为在地方一级最有效和最有益的回应。作为NSF的发言人？作为中西部的大数据中心，我们的努力可以有效地扩展，传播和应用于阿片类药物和其他社会问题，如婴儿死亡率，犯罪和自然灾害。这个项目符合NSF的使命，以促进科学的进步（为大型社会相关网络基础设施的科学和工程做出贡献），以促进美国公民的健康和福利（以新的有用方式将数据源联系起来，使社区有能力解决社会问题;在学术界、工业界、政府和社区之间建立可持续的伙伴关系;提高数据素养和社区对数据科学的参与;通过开发/调整数据分析培训模块和课程来加强研究和教育）。该项目的主要目标是通过BIGDATA（BD）技术帮助中西部的小型和农村社区解决阿片类药物流行病。虽然没有一个社区能够幸免，但小型和农村社区在应对阿片类药物流行病方面面临着独特的挑战：知识和数据存在于多个组织的孤岛中，这些组织的管辖范围各不相同;收集，链接和分析数据的努力受到缺乏基础设施和工具的阻碍;农村地区受到蜂窝连接“死区”的困扰;社区缺乏数据收集和分析的能力。受影响社区的需求和资源并不统一，需要灵活、开放、利用重要社区投入并能尽职验证的BD方法。我们提出的解决方案是OpenOD，这是一个提供统一，相关和及时访问数据的框架。通过与中西部大数据中心（MBDH）和我们的合作伙伴紧密合作，我们的三个主要目标是：（1）与当地社区合作，了解网络基础设施、数据可用性以及对数据分析员工技能的需求方面的优势和差距。(2)组装灵活的网络基础设施，包括数据共享、可供用户使用且适用于云的数据分析和可视化工具，以及具有移动的和非移动的功能的互联网连接。 (3)评估和传播网络基础设施和数据分析工具给整个地区的利益相关者群体，同时促进新的伙伴关系。OpenOD将创建方法，允许管理单位部署公开可用的工具，而不是依赖于专有工具。通过这种方式，有效地解决了在数据访问和随后的反应方面存在的差距。该项目的潜在贡献是：（1）鉴于OpenOD在农村地区的运作环境，提高对BD和STEM的扫盲以及代表性不足群体的社区参与，因为农村地区的人口贫困，缺乏加入现代劳动力的适当技能。(2)通过以新的和有用的方式连接数据源，增强社区应对阿片类药物危机的能力，改善社会中个人的福祉;改善连通性和及时提供关键信息将加快社区的反应速度，并改进预防战略。(3)为研究和教育提供基础设施将得到改善，因为项目活动将向社区利益攸关方、研究人员和教育工作者提供链接的、精心策划的数据集。培训单元和课程经过改编和开发，并与当地/区域教育工作者分享，供资期结束后将继续提供给社区。此外，新的和已建立的伙伴关系将使该项目在社区的长期可持续性。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估的支持。