The maritime dataset, e.g., AIS data, includes both static (ship type, ship affiliation) and dynamic information (speed, course heading, etc.) about the ships, and these datasets are featured as large volume, high dimension, time-dependent, etc. How to extract useful information from these complex datasets is a big challenge for domain experts. To facilitate domain experts' better understanding of their datasets, we propose to combine data mining and visualization techniques together to explore their datasets.