publication . Conference object . Article . Other literature type . 2019

Maritime data integration and analysis: Recent progress and research challenges

Claramunt, C.; Ray, C.; Salmon, L.; Camossi, E.; Hadzagic, M.; Jousselme, A-L.; Andrienko, G.; Andrienko, N.; Theodoridis, Y.; Vouros, G.;
Open Access English
  • Published: 05 Feb 2019
Abstract
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 develo...
Subjects
free text keywords: Big Spatio-temporal Data, Moving Objects, Maritime Information Systems, Event detection, Forecasting, Uncertainty, Big Data, Analytics, Air Traffic Management, Maritime Situational Awareness, Data Management, Visual Analytics, QA75, VM
Related Organizations
Funded by
EC| datACRON
Project
datACRON
Big Data Analytics for Time Critical Mobility Forecasting
  • Funder: European Commission (EC)
  • Project Code: 687591
  • Funding stream: H2020 | RIA
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Other literature type . 2019
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publication . Conference object . Article . Other literature type . 2019

Maritime data integration and analysis: Recent progress and research challenges

Claramunt, C.; Ray, C.; Salmon, L.; Camossi, E.; Hadzagic, M.; Jousselme, A-L.; Andrienko, G.; Andrienko, N.; Theodoridis, Y.; Vouros, G.;