The Cycle Atlanta project aims at creating sensor systems that allow a bike to "see" its environment and collect data as a participatory effort so that we can help the City of Atlanta to make informed decisions about biking infrastructures. Specifically, a sensor box equipped with sonars, lidars, PM sensors, gas sensors, gyroscope, accelerometer, and others was developed to detect environmental factors that can give rise to cyclists' stress level. I participated in this project as a Data Science for Social Good (Atlanta's DSSG) Summer fellow in 2017.
"Poverty maps" are designed to simultaneously display the spatial distribution of welfare and different dimensions of poverty determinants. The plotting of such information on maps heavily relies on data that is collected through infrequent national household surveys and censuses. However, due to the high cost associated with this type of data collection process, poverty maps are often inaccurate in capturing the current deprivation status.
This project aims to build a map-based platform that presents historical documents of the nation-wide, urban renewal project in 1960's and 70's and to provide easy-to-use interfaces that can be used by former residents, archivists, researchers, and citizens. Ultimately, this platform aims to reconstruct a virtual neighborhood where people can share their memories by creating social networks of former residents.
The Center for Open Data Enterprise is a non-profit organization that aims to maximize the value of open data as a public resource that anyone can use. As a means to promote the impact and value of using open data, the center designed and developed the Open Data Impact map. As a Data Science & Technology Fellow at the Center for Open Data Enterprise, I have worked on the Open Data Impact Map, which is a searchable, centralized database of open data use cases from around the world. The map shows the distribution of organizations in the world that make use of open data.
Information accessibility problems include diverse types of human- and system-driven barriers that make it difficult for individuals to access desired information. These issues have been studied in two main streams: (1) a human-centered view based on the understanding of individual-level characteristics such as physical impairment and economic status, and (2) a technology-focused view that emphasizes system-based factors such as the information filtering techniques and interface designs.
This prototype was an intermediate result of a robot-human interaction project conducted at Torooc Inc., a VC-funded start-up company where I was a co-founder and Director of Software Development, in 2011. We started up this company through winning the first-place prize at the 2012 Start-up Competition by Seoul National University R&DB Foundation and Seoul Techno Holdings.
This research project had been conducted for my master's thesis (Master of Information Management degree). I conceptualized cultual background with Hall's high- and low-context culture (1976) and tried to see whether people's perceptions of urban places vary between physical addresses and symbolic representations of spaces (landmarks), when their cultural backgrounds were different. A survey questionnaire was used to measure cultural background, and a web-based online game was used to measure people's perceptions of places.
Geo-local systems can significantly increase users' familiarity with new places. However, for these systems to be useful, geospatial information needs to be presented in ways that those systems can minimize users' difficulties of learning about a new place. This raises a fundamental question about what kinds and representations of geospatial information are effective in making a place more familiar, so that people can adjust to the place more easily even before visiting the unfamiliar world.