EnzymeML is modular: EnzymeML was developed as a container for experimental and modelling data, supporting a seamless data flow between different applications (Fig. ). Data obtained from an experiment and metadata on experimental conditions can be stored by the experimentalist in a spreadsheet, which is convertible into EnzymeML using the API. Longer term, it is hoped that electronic lab notebooks, laboratory information management systems, and enzymology software will support the format. The EnzymeML document contains sufficient experimental data to allow for the estimation of the kinetic parameters by modelling platforms such as COPASI , BioCatNet , or Matlab™. Kinetic parameters can then be included in the EnzymeML document. As a consequence, enzyme assay data may be easily reanalyzed and checked with a range of data fitting algorithms, increasing reusability and confidence in both the experimental data and reported kinetic parameters.