Mass spectrometry-based proteomics and metabolomics are rapidly evolving research fields driven by the development of novel instruments, experimental approaches, and analysis methods. Monolithic analysis tools perform well on single tasks but lack the flexibility to cope with the constantly changing requirements and experimental setups. Workflow systems, which combine small processing tools into complex analysis pipelines, allow custom-tailored and flexible data processing workflows that can be published or shared with collaborators. In this article, we present the integration of established tools for computational mass spectrometry from the open-source software framework OpenMS into the workflow engine KNIME for the analysis of large data sets and production of high quality visualizations. We provide example workflows to demonstrate combined data processing and visualization for three diverse tasks in computational mass spectrometry: isobaric mass tag based quantitation in complex experimental setups, label-free quantitation and identification of metabolites, and quality control for proteomics experiments.This article is protected by copyright. All rights reserved