B0948
Title: Spatio-temporal big data: Managing social media and trajectories
Authors: Martin Werner - Bundeswehr University Munich (Germany) [presenting]
Abstract: The focus is first on spatial big data including organizing global datasets for getting a social media footprint for each individual building on a distributed computer based on randimized data representations and smart fault tolerance. This represents the unique challenges from the volume dimension of big data. In addition, there is a dimension of complexity, which will be shortly illustrated on trajectories by showing some methods with which quadratic and cubic settings (for example nearest neighbors) can be performed in acceptable time. Finally, we give hints on current challenges and future research including the case of quantum computing. In summary, we will discuss examples of solving big spatio-temporal data challenges through parallelization, simplification, and emerging technology.
