Heparin and heparan sulfate (HS) glycosaminoglycans (GAGs) are cell surface polysaccharides that bind to a multitude of signaling molecules, enzymes, and pathogens and modulate critical biological processes ranging from cell growth and development to anticoagulation and viral invasion. Heparin has been widely used as an anticoagulant in a variety of clinical applications for several decades. The heterogeneity and complexity of HS GAGs pose significant challenges to their purification and characterization of structure-function relationships. Nuclear magnetic resonance (NMR) spectroscopy is a promising tool that provides abundant sequence and structure information for characterization of HS GAGs. However, complex NMR spectra and low sensitivity often make analysis of HS GAGs a daunting task. We report the development of a novel methodology that incorporates distinct linkage information between adjacent monosaccharides obtained from NMR and capillary electrophoresis (CE) data using a property encoded nomenclature (PEN) computational framework to facilitate a rapid and unbiased procedure for sequencing HS GAG oligosaccharides. We demonstrate that the integration of NMR and CE data sets with the help of the PEN framework dramatically reduces the number of experimental constraints required to arrive at an HS GAG oligosaccharide sequence.