Data annotation is the process of labeling data to make it usable for machine learning. Data can be almost any kind of data that a human might understand. This includes images (from person, cars, phones, or medical instruments), text (in English, Spanish, Chinese, or any other language), audio, video, 3D models from MRIs and CAT scans, tabular data, time-series data, LIDAR data, RADAR data, or data from other sensors, anything other kind of data you can imagine. There are many different types of data annotation, depending on what kind of form the data is in, and the end-use for machine learning. Some are: semantic annotation, image and video annotation, text categorization, and content categorization.