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Volumes of metabolomics data have been rapidly expanding in recent years, driven by advances in instrumentation, data analysis, and the development of repositories. Even so, the rate of data generation has not kept up with demand, with potential applications in drug discovery, personalised medicine, nutrition, agriculture, analytical chemistry and more all expanding the use case for more information. This collection presents a series of articles describing metabolomics datasets, covering data from any organism type, collected via any valid metabolomic technique, and for any application. All open datasets are presented without hypotheses or significant analyses to support re-use in the aforementioned fields, as per the scope of a Scientific Data Descriptor.

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