Large marine data possesses several typical characteristics, such as large amount, multisource, multiple dimensions, multi-type and so on. How to design an optimal quality inspection plan and control the ocean data timely becomesmore and more important for the application of largemarine data. Based on skyline, it proposed a method to select the optimal quality inspection plan for the quality inspection of large marine data. Firstly, the residual of acceptance quality probability of each quality inspection plans for ocean big data were calculated byHyper-geometric distributionmodel. And then, the optimal quality inspection plan was selected based on the algorithm of block-nested-loops (BNL), which compared the residual of acceptance quality probability of each quality inspection plans one by one. Finally, the proposed method is verified by inspecting the quality of the largemarine data, which is collected bymonitoring sites in a certain sea area.