Nomatic: Location By, For, and Of Crowds

In this paper we present a social and technical architecture which will enable the study of localization from the perspective of crowds. Our research agenda is to leverage new computing opportunities that arise when

many

people are simultaneously localizing themselves. By aggregating this and other types of context information we intend to develop a statistically powerful data set that can be used by urban planners, users and their software. This paper presents an end-to-end strategy, motivated with preliminary user studies, for lowering the social and technical barriers to sharing context information. The primary technology through which we motivate participation is an intelligent context-aware instant messaging client called Nomatic*Gaim. We investigate social barriers to participation with a small informal user study evaluating automatic privacy mechanisms which give people control over their context disclosure. We then analyze some preliminary data from an early deployment. Finally we show how leveraging these mass-collaborations could help to improve Nomatic*Gaim by allowing it to infer position to place mappings.