I-Corps: Workforce development program to complete data wrangling and data labeling tasks

I-Corps：完成数据整理和数据标记任务的劳动力发展计划

• 批准号: 2151840
• 负责人: Elizabeth DiSalvo
• 金额: $ 5万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-15 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2151840&HistoricalAwards=false
• 关键词: Corps; Workforce; development; program; complete

The broader impact/commercial potential of this I-Corps project is the development of a replicable system for more accessible and appropriate digital tools that forms the basis of a service that employs people with little computing education in entry-level technical work. Data collection and use has become ubiquitous in smart communities, but the access to affordable and ethical data workforce is limited. In this I-Corps project, the goal is to investigate customer-centered business models for providing affordable and ethical data services. This potential service will broaden participation in computing by providing work that helps individuals from underrepresented groups develop technical skills. By focusing on data work, participation includes not only engagement with computing but also workforce development to fill a gap for local data expertise. The proposed service also will serve a need in civic and non-profit sectors, providing low cost and ethical data cleaning and preparation for these organizations. This may enable organizations that are serving communities to leverage data in decision making. The plan is to explore client needs, business models, and opportunities to franchise this business model to communities across the United States. There is potential for to serve communities in both rural and urban areas – providing jobs, opportunities for computing careers, and data services to civically engaged organizations. This I-Corps project is based on the development of computational digital tools, including guidelines that are accessible and appropriate for people with little computing experience, to create replicable data work service programs. Through the design and deployment of different data learning pathways, learning in the context of work may be purposefully structured to move underrepresented youth from entry level participation with data science and civic engagement to fuller participation in both data science and civic domains. The proposed tools and design guidelines will involve workers in the development to help ensure more appropriate digital tools for entry-level data work. Importantly, this is accomplished in ways relevant to the target communities as well as to the larger context of digital civics to identify needs for computational data tools that further digital and civic literacy. Existing data tools will be analyzed and an indexed and searchable catalog of data work tools will be developed. Based on this analysis, gaps in tools that are needed may be identified. Prototypes of these data tools will be tested to iteratively improve the design to meet the needs of underserved communities.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.

这个I-Corps项目更广泛的影响/商业潜力是开发一个可复制的系统，用于更容易获得和更适当的数字化工具，形成一种服务的基础，雇用几乎没有计算机教育的人从事初级技术工作。数据收集和使用在智能社区中已经无处不在，但获得负担得起的道德数据劳动力的机会有限。在这个I-Corps项目中，目标是研究以客户为中心的商业模式，以提供负担得起的和道德的数据服务。这项潜在的服务将通过提供帮助来自代表性不足群体的个人发展技术技能的工作来扩大对计算的参与。通过专注于数据工作，参与不仅包括参与计算，还包括劳动力发展，以填补当地数据专业知识的空白。拟议的服务还将满足民间和非营利部门的需求，为这些组织提供低成本和道德的数据清理和准备。这可能使服务于社区的组织能够在决策中利用数据。 该计划旨在探索客户需求、商业模式以及将这种商业模式特许经营到美国各地社区的机会。有潜力为农村和城市地区的社区服务-为公民参与组织提供就业机会，计算机职业机会和数据服务。这个I-Corps项目的基础是开发计算数字化工具，包括可访问和适合于几乎没有计算经验的人的指导方针，以创建可复制的数据工作服务程序。通过设计和部署不同的数据学习途径，可以有目的地构建工作环境中的学习，以使代表性不足的青年从数据科学和公民参与的入门级参与转向更充分地参与数据科学和公民领域。 拟议的工具和设计准则将使工作人员参与开发，以帮助确保为入门级数据工作提供更适当的数字化工具。 重要的是，这是通过与目标社区以及数字公民学的更大背景相关的方式来实现的，以确定对促进数字和公民素养的计算数据工具的需求。将分析现有的数据工具，并将编制一个有索引和可搜索的数据工作工具目录。根据这一分析，可以确定所需工具的差距。这些数据工具的原型将被测试，以迭代地改进设计，以满足服务不足社区的需求。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智力价值和更广泛的影响审查标准进行评估的支持。