The availability of mobility data for scientific analysis has vastly increased, driven by the emergence of inexpensive GNSS recording hardware such as cell phones and small data loggers. Oftentimes, mobility data, which usually contains GNSS coordinates, timestamps, and other sensor measurements, needs to be augmented with additional spatial data in order to derive meaningful information and to facilitate human comprehensibility. Hence, processes like map-matching, geocoding, and routing are standard tools used in mobility data analysis. Unfortunately, available open-source solutions providing such services are heterogeneous in syntax, as well as in in-/output formats and do not offer all the functionalities needed throughout mobility data analysis. This paper presents MAGIS (Mobility Analysis GIS), a software architecture which harmonizes the syntax and usage of existing open-source GIS solutions, bundles their functions under one interface, and ensures data consistency along the tool chain.
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The availability of mobility data for scientific analysis has vastly increased, driven by the emergence of inexpensive GNSS recording hardware such as cell phones and small data loggers. Oftentimes, mobility data, which usually contains GNSS coordinates, timestamps, and other sensor measurements, needs to be augmented with additional spatial data in order to derive meaningful information and to facilitate human comprehensibility. Hence, processes like map-matching, geocoding, and routing are sta...
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