Reproducibility is one of the main goals of FAIR principles, especially for reuse of the workflow for different datasets. The collection of provenance is essential for reproducibility. This calls for a need for standards and ontologies requirements in metabolomics studies to specify the type and format of metadata collected from the workflow as a research object (prospective provenance), but also the execution of the workflow and its results from a particular metabolomics dataset (retrospective provenance) to track the dataflow . The next major phase for the FAIRification of the metabolomics workflow is to define minimum requirements/standards and ontologies for metabolomics data analysis provenance collection. Once the minimum requirements reporting for metabolomics workflows and the results obtained from these workflows are attained, the FAIR principles will be adapted to the new data objects and ontologies.