We explore an idea of transferring some classic measures of global dependence between random variables Χ_1, Χ_2, L_, Χ_n into cumulative measures of dependence relative at any point (χ₁, χ₂, L, χ_n) in the sample space. It allows studying the behavior of these measures throughout the sample space, and better understanding and use of dependence. Some examples on popular copula distributions are also provided.