Do we need more data or better data? The importance of data quality for research reliability

In recent decades, the awareness of how fundamental data management is to guarantee the reliability and reproducibility of research results has significantly increased, in parallel with the ability to collect increasingly large volumes of data. In 2016, the FAIR principles for scientific data management were proposed for the first time, as a guideline to ensure the reusability of data by both humans and machines and enable machine learning/AI-based analytical approaches. During this lesson, starting from the definition of the FAIR principles, I will explain how their adoption is functional to the production of high-quality reliable data, also in the context of the recent explosion in the use of Artificial Intelligence.