default Big data architectures in support of computational maritime situational awareness: case study in port traffic analysis

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Big data architectures in support of computational maritime situational awareness: case study in port traffic analysis.Cazzanti, Luca; Davoli, Antonio. CMRE-FR-2015-021. December 2015.

Computational Maritime Situation Awareness (MSA) supports the maritime industry, governments, and international organizations with machine learning and statistical data analysis techniques for analyzing vessel traffic data. A critical challenge of scaling computational MSA to big data regimes is integrating the core learning algorithms with big data technologies while taking into account the semantics of the maritime domain and the needs of the stakeholders. To address this challenge, this report surveys the concepts and technologies from the field of big data and describes why and how they may support the typical tasks and challenges faced by the MSA community. As a concrete, practical example of how big data can support MSA, this report describes a software tool developed by the Centre for Maritime Re-search and Experimentation (CMRE) according to big data principles that analyses large quantities of open source, maritime vessel traffic data, produces summary statistics of activities in ports, and makes them available to end users in easy-to-understand charts.