With the advancements in omics technologies, there is an exponential increase in digital data volume . The relatively new omics field, metabolomics, is the analysis of small molecules, also known as metabolites, from biological samples such as cells, tissues, or organisms, which gives insights into biological phenomena and has applications ranging from drug discovery to ecosystem monitoring . The untargeted metabolomics experiments acquire thousands of features from the samples that are difficult to reproduce with different mass spectrometry instruments (described in Section 3) . The FAIRification of metabolomics workflows can address some of the challenges, including data complexity and reproducibility in metabolomics, which can help researchers share their results in a more FAIR-compliant way. Here, we demonstrate the application of the FAIR guidelines to a metabolomics workflow as an illustrative example.