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Porous graphitized carbon (PGC) based chromatography achieves high-resolution separation of glycan structures released from glycoproteins. This approach is especially valuable when resolving structurally similar isomers and for discovery of novel and/or sample-specific glycan structures. However, the implementation of PGC-based separations in glycomics studies has been limited because system-independent retention values have not been established to normalize technical variation. To address this limitation, this study combined the use of hydrolyzed dextran as an internal standard and Skyline software for post-acquisition normalization to reduce retention time and peak area technical variation in PGC-based glycan analyses. This approach allowed assignment of system-independent retention values that are applicable to typical PGC-based glycan separations and supported the construction of a library containing >300 PGC-separated glycan structures with normalized glucose unit (GU) retention values. To enable the automation of this normalization method, a spectral MS/MS library was developed of the dextran ladder, achieving confident discrimination against isomeric glycans. The utility of this approach is demonstrated in two ways. First, to inform the search space for bioinformatically predicted but unobserved glycan structures, predictive models for two structural modifications, core-fucosylation and bisecting GlcNAc, were developed based on the GU library. Second, the applicability of this method for the analysis of complex biological samples is evidenced by the ability to discriminate between cell culture and tissue sample types by the normalized intensity of N-glycan structures alone. Overall, the methods and data described here are expected to support the future development of more automated approaches to glycan identification and quantitation.