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Facing an increasing amount of movements at sea and daily impacts on ships, crew and our global ecosystem, many research centers, international organizations, industrials have favored and developed sensors, detection techniques for the monitoring, analysis and visualization of sea movements. Automatic Identification System (AIS) is one of these electronic systems that enable ships to broadcast their dynamic (position, speed, destination...) and static (name, type, international identifier…) information via radio communications.
Having spatially and temporally aligned maritime dataset relying not only on ships' positions but also on a variety of complementary data sources is of great interest for the understanding of maritime activities and their impact on the environment.
Our public dataset contains ships' information collected though the Automatic Identification System, integrated with a set of complementary data having spatial and temporal dimensions aligned. The dataset contains four categories of data: Navigation data, vessel-oriented data, geographic data, and environmental data. It covers a time span of six months, from October 1st, 2015 to March 31st, 2016 and provides ships positions within Celtic sea, the Channel and Bay of Biscay (France). The dataset is proposed with predefined integration and querying principles for relational databases. These rely on the widespread and free relational database management system PostgreSQL, with the adjunction of the PostGIS extension, for the treatment of all spatial features proposed in the dataset.
Follow this link to access the data paper : https://doi.org/10.1016/j.dib.2019.104141 (https://www.sciencedirect.com/science/article/pii/S2352340919304950 )
Follow this link to access the dataset: https://doi.org/10.5281/zenodo.1167594
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