I am an Assistant Professor in the Computer Science Department at American University. My research is focused on using information visualization and novel interaction techniques to make civic data more accessible. My work has been published at IEEE VIS, EuroVIS, HICSS, HFES, and more.
Citizen participation can provide valuable insight into data that is not captured by official sources. In this paper, we propose a technique for using mental maps consisting of three fundamental elements: nodes, paths, and edges. These elements can be used to augment crime data analysis in urban spaces by incorporating the values and knowledge of citizens. We apply this technique to an analysis of property crime in three US cities: Baltimore, Atlanta, and Chicago. Subsequently, we find these cities have neighborhoods where the crime could be substantially higher---or perceived by citizens as higher---than is accounted for in the official public crime data. This analysis can be a vital first step for identifying hidden hotspots or better understanding public perceptions of high crime. [link]Short paper, EuroVis '17
Analyzing the important events and news stories that have captured the public interest in a city can be useful for determining the topics that are vital to the people that live there. Social media data, such as tweets, provides a useful and ever-churning feed of data to analyze for this purpose. For even a moderately-sized city, however, individual neighborhoods can have very different characteristics from one another. Geotagged tweets can be a rich data source for determining what people are saying online about the location they are in. Relating the text data to spatial location, however, presents a unique challenge in representation and layout. In this paper, we introduce TypoTweet Maps: a technique for constructing representations of neighborhood topics as typographic maps. TypoTweet Maps show differences in neighborhood topics using only text, avoiding the channel interference of feature labels that are unnecessary for residents who are familiar with the shape of the city. We describe the process of mapping geotagged tweets to the shape of neighborhoods and streets, and present a case study applying the technique to the city of Atlanta. [link]Short paper, EuroVis '17
During the course of a day, a police unit is expected to move throughout the city to provide a visible presence and respond quickly to emergencies. Planning this movement at the beginning of the shift can provide a helpful first step in ensuring that officers are present in areas of high crime, but these plans can quickly break down as they are pulled away to 911 calls. Once such an initial plan is deferred, police units need to be able to rapidly and fluidly decide where to go next depending on their immediate location and time. In this paper, we present our research to couple spatiotemporal analysis of historical crime data with sketch-based interaction methods. This research is presented through an initial prototype, HotSketch, which we describe through a set of use cases within the domain of police patrol route planning. [link]Conference paper, Best paper nominee, HICSS '17