Data dependent acquisition (DDA) methods have been the workhorse of protein/peptide identification by mass spectrometry, however, the stochastic ion selection process creates randomness that has been discussed numerous times. Also, as proteomic matrices are so complex, there is a proportion of MS/MS spectra with co-isolated precursor ions which is very difficult to deconvolute and can create identification confidence issues.Data independent acquisition (DIA) methods provide a route to deconvolute the MS/MS and generate a more robust and reproducible compound identification list. This paper describes DIA methods that provide excellent reproducible protein lists from samples which far improve on the reproducibility of DDA and also far increase our depth of coverage in a single proteomic sample.