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Lameness is one of the costliest pathological problems affecting dairy animals. It is usually assessed by trained veterinary clinicians who observe features such as gait symmetry or gait parameters as step counts in real time. With the development of artificial intelligence, various modular systems have been proposed to minimize subjectivity in lameness assessment. However, the major limitation in their development is the unavailability of a public database, as most existing ones are either commercial or privately held. To tackle this limitation, we have introduced CowScreeningDB, a multi-sensor database which was built with data from 43 dairy cows. Cows were monitored using smart watches during their normal daily routine. The uniqueness of the database lies in its data collection environment, sampling methodology, detailed sensor information, and the applications used for data conversion and storage, which …