Uncertainty in geosocial data

Abstract

In data management, uncertainty and lack of information are commonly considered as hurdles to overcome. But when it comes to management of geosocial data, where data can be used to associate people with geographic locations they visited, uncertainty is frequently not just an obstacle but also a desired feature. Uncertainty and lack of information---such as knowing only approximate locations of users or knowing only some of the locations users visited---may reduce the accuracy of data analysis. They, however, may be desired, or even required, for keeping user privacy, and for using data that otherwise would not have been collected and used. Due to the heterogeneity of geosocial data, uncertainty is prevalent in geosocial applications, and should not be overlooked. In this paper, we discuss some of the causes of uncertainty in geosocial data management. We elaborate on some of the advantages and disadvantages of using inaccurate or incomplete geosocial data, and we illustrate some of the methods to cope with uncertainty in geosocial applications.