In recent years, the adoption of the FAIR principles has achieved notable success. This progress has led to the development of numerous assessment tools originating from diverse fields of application, thus addressing diverse object types, interpretations and implementa- tions. Given the plethora of proposals available, it is crucial for users to precisely understand these measures, compare them effectively, make informed choices, and accurately interpret the obtained measurements. To meet these needs, we propose a model to formally represent and an- alyze measures. Besides the benefit of homogenization, it allows for the formal definition of three characteristic quantities: coverage, granularity and impact. Our experiments show how these quantities (i) contribute to explain different scores obtained by digital artifacts using two different state-of-the-art assessment engines, (ii) enable a comparative study of different FAIRness measures, independently of any digital artifact.