Managing uncertainty in spatial and spatio-temporal data
Reynold C. K. Cheng, Tobias Emrich, Hans‐Peter Kriegel, Nikos Mamoulis, Matthias Renz, Goce Trajcevski, Andreas E Züfle · 2014
Location-related data has a tremendous impact in many applications of high societal relevance and its growing volume from heterogeneous sources is one true example of a Big Data [1]. An inherent property of any spatio-temporal dataset is uncertainty due to various sources of imprecision. This tutorial provides a comprehensive overview of the different challenges involved in managing uncertain spatial and spatio-temporal data and presents state-of-the-art techniques for addressing them.