Kuang Chen- Data in the First Mile
In many disadvantaged communities worldwide, local low-resource organizations strive to improve health, education, infrastructure, and economic opportunity. These organizations struggle with becoming data-driven because their communities still live outside of the reach of modern data infrastructure, which is crucial for delivering effective modern services. In this talk, we summarize some of the human, institutional and technical challenges that hinder effective data management in "first mile" communities. We propose a set of directions, including 1) separating the capture of data from its structuring, 2) applying intelligent automation to mitigate human, institutional and infrastructural constraints, and 3) deploying services in cloud infrastructure, opening up further opportunities for human and computational value addition. We illustrate these ideas in action with two projects: Usher, a system for automatically improving data entry quality based on prior data, and Shreddr, a hosted paper form digitization service.