EnzymeML enables data publication in compliance with FAIR principles: An EnzymeML document stores comprehensive information about data and metadata of an enzymatic experiment: the experimental conditions, the time course of substrate and product concentration, the kinetic model, and the estimated kinetic parameters, thus making the experiment and its analysis reproducible. Upon publication, it is recommended to use EnzymeML documents as supplementary material. By depositing EnzymeML documents on platforms such as FAIRDOMHub or Dataverse 37 using a digital object identifier, EnzymeML documents are findable and accessible. EnzymeML documents also include references to the scientific publications from which they arose, providing contextual information.