Recent advances in O-glycoproteomics strategies have resulted in substantial progress in identification and characterization of O-glycoproteins, and this is particularly true for the mucin-type or GalNAc-type O-glycosylation. Highthroughput mass spectrometric methods have produced large quantities of O-glycosite data, allowing us to finally produce more comprehensive maps of sites of O-glycosylation. In this chapter we discuss this explosion of data, the implication it has upon our understanding of the nature of GalNAc-type O-glycosylation, and the development of bioinformatic tools to aid our comprehension of the O-glycoproteome. As tools to aid comprehension, predictors of O-glycosylation such as NetOGlyc4.0 allow us to make estimates about the nature of the complete O-glycoproteome, while tools such as the Glyco Domain Viewer help us focus on individual proteins and better understand the protein context of the glycosites. We explore some of the concepts that surround these bioinformatics tools and provide some perspective as to how these tools can be further developed to support the study of glycosylation in biology and medicine.