The correlated exploitation of heterogeneous data sources offering very large historical as well as streaming data is important to increasing the accuracy of computations when analysing and predicting future states of moving entities. This is particularly critical in the maritime domain, where online tracking, early recognition of events, and real-time forecast of anticipated trajectories of vessels are crucial to safety and operations at sea. The objective of this paper is to review current research challenges and trends tied to the integration, management, analysis, and visualization of objects moving at sea as well as a few suggestions for a successful development of maritime forecasting and decision-support systems.

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The different versions of the original document can be found in:

http://dx.doi.org/10.5281/zenodo.2557431 under the license http://creativecommons.org/licenses/by/4.0/legalcode
http://dx.doi.org/10.5281/zenodo.2557432 under the license http://creativecommons.org/licenses/by/4.0/legalcode

DOIS: 10.5281/zenodo.2557432 10.5441/002/edbt.2017.18 10.5281/zenodo.2557431

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Published on 01/01/2019

Volume 2019, 2019
DOI: 10.5281/zenodo.2557432
Licence: Other

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