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Respiratory cilia are important components in the lung defense mechanism. The coordinated beating of cilia cleans the airways of pathogens and foreign particles. We present a large-scale validation dataset of cilia motion for characterizing ciliary function. Ciliary beat frequency (CBF) is provided as benchmark metrics. The video dataset of cilia motion phenotypes contains four categories: temperatures, drugs and ACE2 manipulation. Under each category, mouse trachea samples were treated with different stimuli and imaged with a high-speed video microscope to acquire cilia motion. In addition, we generate ground truth masks labeling ciliary area for image segmentation. This validation dataset can serve as a benchmark for the computer vision community to develop models for analyzing ciliary beat pattern. This video dataset contains 872 videos and their ground-truth masks with the ciliary area labeled. The videos were recorded at 250 frames per second for 1 second. The image size is 800x800. Each pixel is 0.07987 μm. The csv file contains the CBF values of each video.