  In recent years, maritime safety and efficiency become more and more
important across the world. Automatic Identification System (AIS) tracks vessel
movement by onboard transceiver and terrestrial and/or satellite base station.
The data collected by AIS contains broadcast kinematic information and static
information. Both of them are useful for anomaly detection and route prediction
which are key techniques in intelligent maritime research area. This paper is
devoted to construct a standard AIS database for maritime trajectory learning,
prediction and data mining. A path prediction algorithm is tested on this AIS
database and the testing results show this database can be used as a
standardized training resource for different trajectory prediction algorithms
and other AIS data mining algorithms.
