Knowledge Resource Center for Ecological Environment in Arid Area
| 项目编号 | 1816080 |
| CHS: Small: Collaborative Research: Making Information Deserts Visible: computational models, disparities in civic technology use, and urban decision making | |
| Erik Johnston | |
| 主持机构 | Arizona State University |
| 开始日期 | 2018-09-15 |
| 结束日期 | 2021-08-31 |
| 资助经费 | 155362(USD) |
| 项目类别 | Continuing Grant |
| 资助机构 | US-NSF（美国国家科学基金会） |
| 项目所属计划 | HCC-Human-Centered Computing |
| 语种 | 英语 |
| 国家 | 美国 |
| 英文简介 | This research will develop a foundational tool for understanding how civic technologies are used and how information inequalities manifest in a city. User data from new civic technologies that reveal inequalities in the information environments of citizens has only recently become available. Since a large portion of data is demographically or geospatially biased due to varying human-data relationships, computational social scientists have used data modeling and algorithmic techniques to adjust the data and remove biases during data-processing. However, this approach limits our understanding of how and why biased information is created, and our ability to address urban information inequalities and biased data-creation. Consequently, as cities transition to e-government enabled by information and communication technology, they may project the inequities of the past into the smart cities of the future, so a fresh approach is needed. This innovative research analyzes and visualizes data from Boston's 311 system for reporting non-emergency issues to the city government, using computational and qualitative approaches to identify, categorize, and understand the kinds of information disparities that are becoming institutionalized by crowdsourced municipal systems, inhibiting smart city transitions, and perpetuating information deserts. For Boston and its citizens, this research could improve both the function and the equity of the city's 311 system. The resulting insights and tools could also inform other cities' implementation of smart city technologies, identify potential distortions in existing urban datasets, and surface potential corrections that could improve decision making and equitable delivery of services for all residents. The research will be performed in three phases. First, six years of civic, census, and geospatial data will be combined with interviews with users, then analyzed to discover the socio-technical dimensions of "information deserts," which are conceptual and physical spaces where local information is poorly embedded in diverse infrastructures and/or less available than in other areas of a city. This research will develop a conceptual model to determine where and how information deserts are located, identify a typology of information deserts based on related community features; and, assess relationships between information deserts and major demographic and geospatial features of data biases. Second, the research team will perform semi-structured interviews with civic stakeholders to gather user requirements for a visual analytics tool as well as to validate the ground truths for the initial models. Based on this, a visual analytics tool will be created to show different types of information deserts, their causes, and anticipated results. Third, through an iterative process the research team will conduct participatory modeling activities with municipality officials and relevant stakeholders to refine the computational models with local contextual information. Also, the usability of the visual analytics tool will be improved with additional user studies. The resulting conceptual and computational models of information deserts will support a refined visual analytics tool that displays information deserts and their characteristics. 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. |
| 来源学科分类 | Computer and Information Science and Engineering |
| URL | https://www.nsf.gov/awardsearch/showAward?AWD_ID=1816080 |
| 资源类型 | 项目 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/341739 |
| 推荐引用方式 GB/T 7714 | Erik Johnston.CHS: Small: Collaborative Research: Making Information Deserts Visible: computational models, disparities in civic technology use, and urban decision making.2018. |
| 条目包含的文件 | 条目无相关文件。 | |||||
| 个性服务 |
| 推荐该条目 |
| 保存到收藏夹 |
| 导出为Endnote文件 |
| 谷歌学术 |
| 谷歌学术中相似的文章 |
| [Erik Johnston]的文章 |
| 百度学术 |
| 百度学术中相似的文章 |
| [Erik Johnston]的文章 |
| 必应学术 |
| 必应学术中相似的文章 |
| [Erik Johnston]的文章 |
| 相关权益政策 |
| 暂无数据 |
| 收藏/分享 |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
