Mass spectrometry (MS) is a key tool for structural analysis of oligosaccharides because of its high accuracy, sensitivity, and speed on one hand and because of the general and flexible protocols on the other. In glycomics projects the analysis of mass spectra is the speed determining step because, unlike in proteomics, software platforms for high-throughput glycan mass spectra interpretation are not fully automated and still depend on highly specialized knowledge. For the publicly available software, initial steps for manual MS data preprocessing are required mostly considering operations with glycan structures already stored in databases. In particular, monoisotopic peaks have to be manually determined or imported. In this contribution we describe our development of a platform for MS data evaluation in glycomics that demands only a low human intervention. The proposed platform named SysBioWare is constructed to allow import of the raw MS data to the spectrum browser and to perform isotopic grouping of detected peaks after de-noising and wavelet analysis. Monoisotopic m/z values render peak list association with the raw MS spectrum and allow compositional assignment according to the tuned building block library. This platform has been applied to human urine glycome as a potent tool for rapid assignment of already known or/and novel structures.