Nowadays, there are many facial expression datasets for expression research. But, these datasets are small amounts of images and little expression information, which limits the expression research. This paper introduces the construction of the facial expression dataset in the wild (FELW) and the test case. The FELW dataset includes many facial expression images, and the images of different age, race and gender are collected from the Internet. Each image includes two labels—the state of facial part label and the expression label, that labeled by the appropriate method. And the author imported Kappa consistency check to improve the recognition rate of the FELW dataset. The author used traditional method and deep learning method to experiment and analysis on this dataset. Compared with other public facial expression datasets, the FELW dataset has much more amounts of images and more varieties of expression, and contains two labels to help to the expression research.