The field of glycoproteomics has experienced considerable growth within the last decade. Analytical improvements in instrumentation, fragmentation, and sample preparation have allowed for biological discoveries in how glycosylation contributes to protein function and cellular health. However, one critical bottleneck in glycoproteomics is data analysis via search algorithms due to the vast heterogeneity in glycosylation. In the first Human Glycoproteomics Initiative study, researchers were sent the same data file and were asked to report glycopeptides found. Unfortunately, vast differences were reported between the groups. Additionally, since then, many new programs and developments have emerged that warrant consideration. Thus, here we propose the second HGI study, wherein developer teams will be sent data files comprising N-glycopeptides, O-glycopeptides, and/or a mixture of both. The results will allow us to recommend suitable settings, parameters, and programs for various sample types. Ultimately, we believe this work will prove useful to the broad glycoproteomics community.