Data annotation is an important term in the fields of artificial intelligence, big data, smart data and automation. Data annotation means "data enrichment". It describes the process by which information or "labels" are added to existing data such as texts, images or videos. This is particularly necessary if machines or computers are to learn to perform tasks independently with the help of artificial intelligence.
One example: If a company wants to develop an AI that recognises cats in photos, many images must first be tagged with the word "cat". Humans look at these images and mark where the cat is located. It is only through this data annotation that computers learn to recognise cats on their own.
Data annotation is therefore a fundamental building block for systems such as language assistants, translation programmes or self-driving cars to function reliably. It ensures that AI systems are trained with the right information and can later deliver accurate results. In times of big data, the importance of data annotation continues to grow and is an important step on the way to automating many processes.
Deutsch 
English (UK)