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Big data analytics for time critical maritime and aerial mobility forecasting

: Vouros, G.A.; Doulkeridis, C.; Santipantakis, G.; Vlachou, A.; Pelekis, N.; Georgiou, H.; Theodoridis, Y.; Patroumpas, K.; Alevizos, E.; Artikis, A.; Fuchs, G.; Mock, M.; Andrienko, G.; Andrienko, N.; Ray, C.; Claramunt, C.; Camossi, E.; Jousselme, A.-L.; Scarlatti, D.; Cordero, J.M.


Böhlen, M.:
Advances in Database Technology - EDBT 2018. 21st International Conference on Extending Database Technology. Proceedings : Vienna, Austria, March 26-29, 2018
Konstanz: Universität Konstanz, 2018
ISBN: 978-3-89318-078-3
International Conference on Extending Database Technology (EDBT) <21, 2018, Vienna>
Fraunhofer IAIS ()

The correlated exploitation of heterogeneous data sources offering very large archival and streaming data is important to increase the accuracy of computations when analysing and predicting future states of moving entities. Aiming to significantly advance the capacities of systems to improve safety and effectiveness of critical operations involving a large number of moving entities in large geographical areas, this paper describes progress achieved towards time critical big data analytics solutions to user-defined challenges in the air-traffic management and maritime domains. Besides, this paper presents further research challenges concerning data integration and management, predictive analytics for trajectory and events forecasting, and visual analytics.