Understanding Movement in Context with Heterogeneous Data

Abstract

Movement data, as captured by myriad sensors, has been growing exponentially. Hence, multidisciplinary approaches for analyzing movement has become feasible. Though, movement pertains to a large variety of domains and applications, the focus of this position paper is understanding human movement (mobility) in various forms. We position maps as heterogeneous, multidimensional and digital representation of reality and advocate their role in contextualizing movement. We overview the main problems for analyzing human mobility with special attention to movement in context, leveraging heterogeneous data. We review the state-of-the-art in solving these problems and describe remaining open problems and challenges for future work. Finally, we offer a view of existing as well as future mapping and location services that could enable these.