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Metabolites are key players in almost all biological processes, and play various functional roles providing energy, building blocks, signaling, communication, and defense. Metabolites serve as clinical biomarkers for detecting medical conditions such as cancer; small molecule drugs account for 90% of prescribed therapeutics. Complete understanding of biological systems requires detecting and interpreting the metabolome in time and space. Following in the steps of high-throughput sequencing, mass spectrometry (MS) has become established as a key analytical technique for large-scale studies of complex metabolite mixtures. MS-based experiments generate datasets of increasing complexity and size. The Dagstuhl Seminar on Computational Metabolomics brought together leading experts from the experimental (analytical chemistry and biology) and the computational (computer science and bioinformatics) side, to foster the exchange of expertise needed to advance computational metabolomics. The focus was on a dynamic schedule with overview talks followed by break-out sessions, selected by the participants, covering the whole experimental-computational continuum in mass spectrometry. Particular focus in this seminar was given to imaging mass spectrometry techniques that integrate a spacial component into the analysis, ranging in scale from single cells to organs and organisms.