The Diversity/similarity measure based on Hasse matrices is a novel chemometric approach based on the partial ordering technique and the Hasse matrix:

- this matrix can be associated to each data sequence and the similarity between two sequences can be evaluated with the definition of a distance between the corresponding Hasse matrices;
- Examples of sequential data are mass spectrometry signals, IR/UV signals, 1D – NMR spectra, electronic nose signals, proteomic maps, DNA sequencies, sequential molecular descriptors. In general, all the spectra achieved along time are intrinsically ordered and can be analysed as sequential data.
- the new proposed distance (weighted standardized Hasse distance) is evaluated between pairs of Hasse matrices derived from the classical partial ordering rules. It can be naturally standardized, thus allowing the interpretation of these distances as absolute values (e.g. percentage) and deriving simple similarity and correlation indices;